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ai/ml research scientist

analytical data scientist

Docusign

<div>
 <strong>
  Company Overview
  <br/>
  <br/>
 </strong>
 Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people&rsquo;s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign&rsquo;s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).
 <br/>
 <br/>
 What you'll do
 <br/>
 <br/>
 Docusign's Product Data Science team is looking for a Data Scientist to support the development of key data products and capabilities to enable data-driven product development and decision making. In this role, you would be part of the Product Data Science team and work directly in partnership with a variety of stakeholders including but not limited to Product, Engineering and User Experience partners to support and empower them with data-driven actionable insights. You will be embedded in specific product spaces requiring you to establish and grow relationships. As a Data Scientist, you&rsquo;ll dig into the data to uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, design experiments and develop data science models to drive customer experience, engagement, and adoption of Docusign&rsquo;s products. If you are an experienced data scientist passionate about data-driven product development and building products and capabilities that enable a culture of &ldquo;test and learn,&rdquo; then this could be a great role for you.
 <br/>
 <br/>
 This position is an individual contributor role reporting to the Director of Product Data Science.
 <br/>
 <br/>
 <strong>
  Responsibility
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Collaborate with cross-functional teams to research, build and improve data analysis to identify opportunities for product improvements, new product features, product utilization, and improve customer experience, engagement, and retention
  </li>
  <li>
   Be the subject matter expert for driving the product data strategy for the areas you support.
  </li>
  <li>
   Partner closely with the product managers, user researchers, engineers, and leadership to capture and prioritize potential insights, analysis, and data product opportunities that will drive maximum business impact
  </li>
  <li>
   Specify and help implement product telemetry, define key performance indicators with goals, and own and manage regular reports to create insights around product usage and success
  </li>
  <li>
   Partner with Global Data Analytics team to automate data pipelines to snowflake from different source systems
  </li>
  <li>
   Design and build automated dashboards that connect data from internal and external data sources, with visualizations and tools that allow business users to self-serve on their website data needs
  </li>
  <li>
   Partner with Product teams to design, administer, and analyze the results of A/B and multivariate tests and other ML models
  </li>
  <li>
   Leverage data to develop actionable analytical insights and present findings to senior management
  </li>
  <li>
   Evangelize models, frameworks, analysis, and insights with stakeholders and business partners
  </li>
  <li>
   Act with a sense of urgency and purpose, identify and resolve roadblocks, reach out to cross-functional team members to solicit input and/or assist when appropriate
   <br/>
   <br/>
  </li>
 </ul>
 Job Designation
 <br/>
 <br/>
 <strong>
  Hybrid:
 </strong>
 Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)
 <br/>
 <br/>
 Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law.
 <br/>
 <br/>
 What you bring
 <br/>
 <br/>
 <strong>
  Basic
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   BA/BS degree in a quantitative field (e.g., Statistics, Math, CS, Economics or Finance) or equivalent work experience
  </li>
  <li>
   2+ years of demonstrated experience with business analytics or product analytics in a data science or analytics role in a SaaS/Cloud industry
  </li>
  <li>
   Experience with pulling data from external sources, joining data from disparate data systems and distilling large data sets into actionable insights that drive business value
  </li>
  <li>
   Experience with SQL for data analysis and data validation
  </li>
  <li>
   Experience with data visualization tools such as Tableau, Power BI, or similar
  </li>
  <li>
   Experience with statistics and rigorous analytical techniques
  </li>
  <li>
   Experience solving real business problems using data and analytics
  </li>
  <li>
   Experience communicating data and technical work to non-technical stakeholders
  </li>
  <li>
   Experience working with Product Engineering and other technical teams to implement the product telemetry requirements
  </li>
  <li>
   Knowledge and experience of agile/scrum product development
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong communication and leadership skills, especially the ability to collaborate cross-functionally and lead through influence across functional and organizational lines
  </li>
  <li>
   Ability to present data in a visual format and explain the insights clearly and concisely
  </li>
  <li>
   Experience with A/B testing, cohort analysis, user segmentation, and other core product analytics methodologies
  </li>
  <li>
   Experience designing and refining machine learning models
  </li>
  <li>
   Experience with Python or R
  </li>
  <li>
   Familiarity with data engineering processes
  </li>
  <li>
   Highly motivated, organized, self-starter who thrives in a fast-paced environment
   <br/>
   <br/>
  </li>
 </ul>
 Wage Transparency
 <br/>
 <br/>
 Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.
 <br/>
 <br/>
 Based on applicable legislation, the below details pay ranges in the following locations:
 <br/>
 <br/>
 California: $100,300.00 - $154,900.00 base salary
 <br/>
 <br/>
 <strong>
  This Role Is Also Eligible For The Following
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
  </li>
  <li>
   Stock: This role is eligible to receive Restricted Stock Units (RSUs).
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 Global benefits provide options for the following:
 <br/>
 <br/>
 <ul>
  <li>
   Paid Time Off: earned time off, as well as paid company holidays based on region
  </li>
  <li>
   Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
  </li>
  <li>
   Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
  </li>
  <li>
   Retirement Plans: select retirement and pension programs with potential for employer contributions
  </li>
  <li>
   Learning and Development: options for coaching, online courses and education reimbursements
  </li>
  <li>
   Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Work Authorization Notice:
 </strong>
 Please note that we do not provide visa sponsorship or immigration support for this position. Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship.
 <br/>
 <br/>
 Life at Docusign
 <br/>
 <br/>
 <strong>
  Working here
  <br/>
  <br/>
 </strong>
 Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what&rsquo;s right, every day. At Docusign, everything is equal.
 <br/>
 <br/>
 We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you&rsquo;ll be loved by us, our customers, and the world in which we live.
 <br/>
 <br/>
 <strong>
  Accommodation
  <br/>
  <br/>
 </strong>
 Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com.
 <br/>
 <br/>
 If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance.
 <br/>
 <br/>
 Applicant and Candidate Privacy Notice
 <br/>
 <br/>
 States Not Eligible for Employment
 <br/>
 <br/>
 This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.
 <br/>
 <br/>
 Equal Opportunity Employer
 <br/>
 <br/>
 It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category.
 <br/>
 <br/>
 EEO Know Your Rights poster
 <br/>
 <br/>
</div>


Data Scientist

University of California - San Francisco

<p></p><div><div><div><div><p>Under direct supervision, acquires skills and knowledge of professional concepts in research data analysis. Works on small projects or segments of projects with limited scope and complexity.<br>
<br>
The specific work will be qualitative data extraction and analysis and assisting with interpretation of overall study findings and preparing materials for data dissemination.<br>
<br>
The final salary and offer components are subject to additional approvals based on UC policy.</p><p>
Your placement within the salary range is dependent on a number of factors including your work experience and internal equity within this position classification at UCSF. For positions that are represented by a labor union, placement within the salary range will be guided by the rules in the collective bargaining agreement.</p><p>
The salary range for this position is $31.47 - $67.19 (Hourly Rate).</p><p>
To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html</p></div>
</div><div><p><b>Department Description</b></p>
<div>Our mission is to prepare students from culturally diverse backgrounds to assume leadership roles in nursing clinical practice, teaching, research, and community service by advancing knowledge and clinical excellence and disseminating it into practice and policy. Faculty members in this department are engaged in cutting-edge research that is improving the quality of care of persons with acute and chronic conditions.</div>
</div><div><p><b>Required Qualifications</b></p>
<div><ul><li>Bachelor's degree in related area and / or equivalent experience / training.</li><li>
Foundational knowledge about the construct of diabetes distress and methods for measurement of this construct</li><li>
Acquiring knowledge of research function. Acquiring ability to perform research analysis duties.</li><li>
Acquiring statistical analysis, systems programming, and database design skills to perform research analysis duties.</li><li>
Ability to effectively manage time and see assigned parts of projects through to completion on deadline.</li><li>
Basic consultation and communication skills.</li></ul></div>
</div><div><p><b>Preferred Qualifications</b></p>
<div><ul><li>Experience with transcription, extraction, analysis, and interpretation of qualitative data</li></ul></div>
</div><div><p><b>About UCSF</b></p>
<div>The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. It is the only campus in the 10-campus UC system dedicated exclusively to the health sciences. We bring together the world&rsquo;s leading experts in nearly every area of health. We are home to five Nobel laureates who have advanced the understanding of cancer, neurodegenerative diseases, aging and stem cells.</div>
</div><div><p><b>Pride Values</b></p>
<div>UCSF is a diverse community made of people with many skills and talents. We seek candidates whose work experience or community service has prepared them to contribute to our commitment to professionalism, respect, integrity, diversity and excellence &ndash; also known as our PRIDE values.
<br>
<br>
In addition to our PRIDE values, UCSF is committed to equity &ndash; both in how we deliver care as well as our workforce. We are committed to building a broadly diverse community, nurturing a culture that is welcoming and supportive, and engaging diverse ideas for the provision of culturally competent education, discovery, and patient care. Additional information about UCSF is available at diversity.ucsf.edu
<br>
<br>
Join us to find a rewarding career contributing to improving healthcare worldwide.</div>
</div><div><p><b>Equal Employment Opportunity</b></p>
<div>The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.</div>
</div><div><p><b>Organization</b></p>
<div>Campus</div>
</div><div><p><b>Job Code and Payroll Title</b></p>
<div>005272 RSCH DATA ANL 1 RP
</div></div><div><p><b>Job Category</b></p>
<div>Research and Scientific</div>
</div><div><p><b>Bargaining Unit</b></p>
<div>Research and Public Service Professionals (RP)
</div></div><div><p><b>Employee Class</b></p>
<div>Limited Appt</div>
</div><div><p><b>Percentage</b></p>
<div>50%</div>
</div><div><p><b>Appointment End Date</b></p>
<div>31-Aug-2026</div>
</div><div><p><b>Location</b></p>
<div>San Francisco, CA
</div></div><div><p><b>Campus</b></p>
<div>Mission Bay (SF)
</div></div><div><p><b>Work Style</b></p>
<div>Flexible</div>
</div><div><p><b>Shift</b></p>
<div>Days</div>
</div><div><p><b>Shift Length</b></p>
<div>Variable</div></div></div></div><div></div>

Research Data Analysis

Uber

<div><b>About the Role</b>
<br>
<br>
Have you ever wondered why it's taking so long for an earner to be matched to your trip, why the ETA is so long, or how an Earner is picked from the many around you? If so, the Mobility Matching Science team is for you!
<br>
<br>
The Matching team at Uber builds the systems that determine the optimal way to fulfill trips on the Mobility platform. We work on the problems of determining which earners to send an offer to and when. The solutions we build are critical for maintaining reliability and ensuring the trust of riders and earners alike.
<br>
<br>
We are looking for experienced scientists who relish the opportunity to develop novel approaches and apply them at Uber's scale. They ideally have a good balance of causal inference, analysis, experimentation, and modeling knowledge, as well as, an ability to use these skills to identify business opportunities and deliver product recommendations.
<br>
<br>
<b>What You'll Do</b>
<ul><li>Develop data-driven business insights and work with cross-functional stakeholders to identify opportunities and recommend prioritization of product, growth and optimization initiatives
</li><li>Design and analyze experiments, communicating results that draw detailed and actionable conclusions
</li><li>Analyze and contribute to development of optimization algos and ML models for use in mobility matching
</li><li>Collaborate with cross-functional teams such as product, engineering and operations to drive system development end-to-end from conceptualization to final product
</li></ul><b>Basic Qualifications</b>
<ul><li>Ph.D. in Statistics, Economics, Machine Learning, Operations Research, Computer Science, or another quantitative field.
</li><li>Minimum 2 years of industry experience as an Applied Scientist, Data Scientist, or in a similar quantitative role.
</li><li>Strong knowledge of the mathematical foundations of statistics, machine learning, optimization, and economics.
</li><li>Proven experience in experimental design (e.g., A/B testing) and causal inference.
</li><li>Proficiency in using Python or R for data analysis, modeling, and algorithm prototyping at scale with large datasets.
</li><li>Experience with exploratory data analysis, statistical analysis and testing, and model development.
</li></ul>Preferred Qualifications
<ul><li>Ph.D., or M.S. in Statistics, Economics, Machine Learning, Operations Research, Computer Science, or another quantitative field.
</li><li>Minimum 5 years of industry experience as an Applied Scientist, Data Scientist, or in a similar quantitative role.
</li><li>Strong knowledge of the mathematical foundations of statistics, machine learning, optimization, and economics.
</li><li>Proven experience in experimental design (e.g., A/B testing) and causal inference.
</li><li>Proficiency in using Python or R for data analysis, modeling, and algorithm prototyping at scale with large datasets.
</li>Experience with exploratory data analysis, statistical analysis and testing, and model development.<br>
<li>
</li></ul><br>
<br>
For San Francisco, CA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Sr. Scientist - Mobility Matching

Decagon

<div>
 <strong>
  About Decagon
  <br/>
  <br/>
 </strong>
 Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.
 <br/>
 <br/>
 Our technology enables industry-defining enterprises like Avis Budget Group, Block&rsquo;s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.
 <br/>
 <br/>
 We&rsquo;re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We&rsquo;re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.
 <br/>
 <br/>
 We&rsquo;re an in-office company, driven by a shared commitment to excellence and velocity. Our values &mdash; Just Get It Done, Invent What Customers Want, Winner&rsquo;s Mindset, and The Polymath Principle &mdash; shape how we work and grow as a team.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 As a Data Scientist at Decagon, you&rsquo;ll bring deep technical rigor to how data is analyzed, tested, and applied across the business. You&rsquo;ll design and interpret experiments, apply advanced statistical methods, and build scalable analytical frameworks that directly inform product strategy and company performance.
 <br/>
 <br/>
 You&rsquo;ll work across Engineering and Product to establish robust measurement practices, expand the use of data-driven decision making, and uncover insights that shape Decagon&rsquo;s trajectory. This role blends strong analytical expertise with product acumen and the ability to influence at the highest levels.
 <br/>
 <br/>
 <strong>
  In this role, you will
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Build and maintain foundational datasets and metrics that reflect infrastructure usage, system performance, and scaling efficiency across Decagon's AI platform.
  </li>
  <li>
   Enhance and extend Decagon&rsquo;s data models, metrics, and dashboards to ensure consistent, scalable reporting across teams.
  </li>
  <li>
   Partner closely with Engineering to shape strategy through data &mdash; surfacing bottlenecks, inefficiencies, and scaling risks before they become problems.
  </li>
  <li>
   Collaborate with Product and Engineering to embed experimentation and measurement best practices into product development cycles.
  </li>
  <li>
   Build and continuously improve Decagon&rsquo;s data stack, ensuring scalable models, pipelines, and tools that empower self-serve analytics across the company.
  </li>
  <li>
   Communicate findings clearly and persuasively to executives and cross-functional stakeholders, influencing strategic decision-making.
  </li>
  <li>
   Conduct deep-dive quantitative investigations to support incident analysis, reliability improvements, and post-mortem learnings.
  </li>
  <li>
   Evaluate and interpret the performance of ML models (e.g., classification, recommendation, LLM-based systems), helping the team reason through trade-offs, limitations, and business implications of model-driven decisions.
  </li>
  <li>
   Be the primary driver of experimentation culture at Decagon, helping define how we design, measure, and scale experiments across the business.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We're Looking For
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong ability to structure ambiguous problems, translate them into analytical approaches, and deliver business impact through data.
  </li>
  <li>
   Advanced proficiency in SQL and Python, with a solid foundation in statistics and experimental design.
  </li>
  <li>
   5+ years (or equivalent experience) in data science or product analytics roles, ideally within high-scale consumer or marketplace products.
  </li>
  <li>
   Ability to reason about and analyze machine learning models, understanding their assumptions, trade-offs, and impact on product and customer outcomes.
  </li>
  <li>
   Proven track record as a data partner in large-scale backend or infrastructure systems.
  </li>
  <li>
   Comfort building operational analytics (e.g., alerting, SLIs/SLOs) and partnering closely with data and infra engineering.
  </li>
  <li>
   Excellent communication skills, with experience influencing stakeholders and driving decisions across teams.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Medical, dental, and vision benefits
  </li>
  <li>
   Take what you need vacation policy
  </li>
  <li>
   Daily lunches, dinners and snacks in the office to keep you at your best
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Compensation
  <br/>
  <br/>
 </strong>
 $250k - $300k + equity
</div>


Senior Data Scientist

GoodLeap

<div><div>About GoodLeap:</div><div>
GoodLeap is a technology company delivering best-in-class financing and software products for sustainable solutions, from solar panels and batteries to energy-efficient HVAC, heat pumps, roofing, windows, and more. Over 1 million homeowners have benefited from our simple, fast, and frictionless technology that makes the adoption of these products more affordable, accessible, and easier to understand. Thousands of professionals deploying home efficiency and solar solutions rely on GoodLeap&rsquo;s proprietary, AI-powered applications and developer tools to drive more transparent customer communication, deeper business intelligence, and streamlined payment and operations. Our platform has led to more than $30 billion in financing for sustainable solutions since 2018.</div><div>
</div><div>
GoodLeap is also proud to support our award-winning nonprofit, GivePower, which is building and deploying life-saving water and clean electricity systems, changing the lives of more than 1.6 million people across Africa, Asia, and South America.</div><div></div><h4 class="jobSectionHeader"><b><br>
Position Summary</b></h4>
<p>
We are seeking a Staff Data Scientist with experience owning data science roadmaps and influencing stakeholders to guide the business strategy. Our ideal candidate is impact-oriented, comfortable balancing competing priorities, and skilled at working independently with both product and business stakeholders. In this role, you will scope, prioritize, and execute analysis projects that will uncover opportunities, inform investments, and drive accountability for results. You will also work closely with other members of the Analytics team on foundational projects to empower analysts and business users across the company with more and easier access to data.</p>
<h3 class="jobSectionHeader"><b>
Essential Job Duties &amp; Responsibilities</b></h3><div>
<div>
<ul><li><p>Work with stakeholders to scope and prioritize analysis and modeling projects that will drive impact and guide business and product decisions</p>
</li>
</ul></div><div><ul><li><p>Develop metrics that are informative, responsive, and relevant to stakeholder teams&rsquo; actions</p>
</li>
</ul></div><div><ul><li><p>Design and execute rigorous, actionable analyses and data modeling projects, using appropriate statistical methods to validate hypotheses and/or production actionable predictions and prescriptions</p>
</li>
</ul></div><div><ul><li><p>Communicate analysis and modeling results effectively to non-technical stakeholders and represent data perspective in strategy and architecture conversations</p>
</li>
</ul></div><div><ul><li><p>Work with stakeholder teams to identify key assumptions in business strategy and/or business opportunities addressable through data modeling and develop plans for using data to learn quickly and deliver results</p>
</li>
</ul></div><div><ul><li><p>Work with product and business teams to develop and execute measurement plans for new initiatives and/or model deployments, including selecting success metrics, reviewing instrumentation and measurement plans, and developing launch reporting</p>
</li>
</ul></div></div><h3 class="jobSectionHeader"><b>Required Skills, Knowledge &amp; Abilities
</b></h3><div><div><ul><li><p>MS in DS, Statistics, or related technical degree or equivalent work experience</p>
</li>
</ul></div><div><ul><li><p>6-10 years' experience as a Data Scientist or in a similar role</p>
</li>
</ul></div><div><ul><li><p>5+ years' hands-on SQL experience in a work environment</p>
</li>
</ul></div><div><ul><li><p>Experience with data modeling and/or casual inference, as appropriate for role</p>
</li>
</ul></div><div><ul><li><p>Experience with statistical programming in Python (numpy, pandas) or R</p>
</li>
</ul></div><div><ul><li><p>Experience with building reports and visualizations to represent data intuitively in Tableau or similar data visualization tools</p>
</li>
</ul></div><div><ul><li><p>Demonstrated ability to work cross-functionally and communicate with technical and non-technical teams</p>
</li>
</ul></div><div><ul><li><p>Demonstrated ability to work with stakeholders to translate business questions into rigorous and actionable data projects</p>
</li>
</ul></div><div><ul><li><p>Experience owning, prioritizing, and communicating an analysis and/or data modeling roadmap for a business area</p>
</li>
</ul></div></div><div>In addition to the above salary, this role may be eligible for a bonus and equity.</div><div><b>
Additional Information Regarding Job Duties and Job Descriptions:</b></div><div></div><div><br>
Job duties include additional responsibilities as assigned by one's supervisor or other managers related to the position/department. This job description is meant to describe the general nature and level of work being performed; it is not intended to be construed as an exhaustive list of all responsibilities, duties and other skills required for the position. The Company reserves the right at any time with or without notice to alter or change job responsibilities, reassign or transfer job position or assign additional job responsibilities, subject to applicable law. The Company shall provide reasonable accommodations of known disabilities to enable a qualified applicant or employee to apply for employment, perform the essential functions of the job, or enjoy the benefits and privileges of employment as required by the law.</div><div></div><div><b><br>
If you are an extraordinary professional who thrives in a collaborative work culture and values a rewarding career, then we want to work with you! Apply today!</b></div><div></div><div><br>
We are committed to protecting your privacy. To learn more about how we collect, use, and safeguard your personal information during the application process, please review our <b>Employment Privacy Policy</b> and <b>Recruiting Policy on AI</b>.</div>
<p>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</p></div>

Staff Data Scientist, Business Solutions

Braze

<div>
 At Braze, we have found our people. We&rsquo;re a genuinely approachable, exceptionally kind, and intensely passionate crew.
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 We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity &ndash; inside and outside our organization.
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 To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.
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 Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.
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 If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can&rsquo;t wait to meet you.
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  What You'll Do
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 As our customer base continues to grow with the excitement around BrazeAI, we&rsquo;re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:
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   Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
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   Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
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   Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
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   Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
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   Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success
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  Who You Are
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   Education: Bachelor&rsquo;s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master&rsquo;s or PhD in a relevant technical discipline preferred
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   Experience: 3&ndash;5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
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   Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
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   Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
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   Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms
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   Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
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   Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
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   Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
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   Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences
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 For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $124,200 - $148,500/year with an expected On Target Earnings (OTE) between $138,000 - $165,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, Braze offers full- and part- time employees a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that all Braze employees own a piece of our company.
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  What We Offer
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 Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here . More details on benefits plans will be provided if you receive an offer of employment.
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  Benefits
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 From offering comprehensive benefits to fostering hybrid ways of working, we&rsquo;ve got you covered so you can prioritize work-life harmony. Braze offers benefits such as:
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   Competitive compensation that may include equity
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   Retirement and Employee Stock Purchase Plans
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   Flexible paid time off
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   Comprehensive benefit plans covering medical, dental, vision, life, and disability
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   Family services that include fertility benefits and equal paid parental leave
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   Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
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   A curated in-office employee experience, designed to foster community, team connections, and innovation
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   Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
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   Employee Resource Groups that provide supportive communities within Braze
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   Collaborative, transparent, and fun culture recognized as a Great Place to Work&reg;
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  About Braze
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 Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging.&trade; Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI&trade; allows marketers to combine and activate AI agents, models, and features at every touchpoint throughout the Braze Customer Engagement Platform for smarter, faster, and more meaningful customer engagement. From cross-channel messaging and journey orchestration to Al-powered decisioning and optimization, Braze enables companies to turn action into interaction through autonomous, 1:1 personalized experiences.
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 The company has repeatedly been recognized as a Leader in marketing technology by industry analysts, and was voted a G2 &ldquo;Best of Marketing and Digital Advertising Software Product&rdquo; in 2025.
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 Braze was also named a 2025 Best Companies To Work For by U.S. News &amp; World Report, a 2025 America&rsquo;s Greatest Companies by Newsweek, and a 2025 Fortune Best Workplace in Technology&trade; by Great Place To Work&reg;, among other accolades. Braze is also proudly certified as a Great Place to Work&reg; in the U.S., the UK, Australia, and Singapore.
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 The company is headquartered in New York with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, S&atilde;o Paulo, Singapore, Seoul, Sydney and Tokyo.
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  BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER
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 At Braze, we strive to create equitable growth and opportunities inside and outside the organization.
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 Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're committed to offering all candidates a fair, accessible, and inclusive experience &ndash; regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you .
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 We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we&rsquo;d love to meet you.
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 Please see our Candidate Privacy Policy for more information on how Braze processes your personal information during the recruitment process and, if applicable based on your location, how you can exercise any privacy rights.
</div>


Forward-Deployed Data Scientist

Owner.com

<p></p><div><p><b>About </b><b>Owner.com</b></p><p>
Owner is the AI growth system for local restaurants.</p><p></p><p><br>
Our AI continuously improves SEO, marketing, and online ordering to grow first-party orders. Unlike other companies that force small business owners to master their software to drive sales, Owner gives them a proven system run by experts.</p><p></p><p><br>
Owner is like having an army of engineers and marketers on your side, just like the big chains.</p><p></p><p><b><br>
Our vision</b></p><p>
We&rsquo;re starting by helping independent restaurants succeed online.</p><p></p><p><br>
But it&rsquo;s not just restaurants that need our help. Most local businesses are struggling with these same problems. Huge technology corporations are taking their customers, bleeding their profits, and making it hard for them to survive.</p><p></p><p><br>
Once we nail the solution for restaurants &ndash; we&rsquo;ll scale it into every other local business type.</p><p></p><p><br>
In the future we envision, tens of millions of local business owners will use our technology to succeed in the digital age.</p><p></p><p><br>
Read our Series C memo here</p><p></p><p><b><br>
Our traction</b></p><p>
Since 2020, we've generated tens of millions in revenue and processed over half a billion dollars of online orders. 1 in 5 Americans have used an Owner.com website.</p><p></p><p><br>
More importantly, we&rsquo;ve helped over 20,000 restaurant owners, and saved them nearly $200 million in fees.</p><p></p><p><b><br>
Our team</b></p><p>
Our team is now in the low hundreds. We&rsquo;ve got top talent from the most successful companies in SMB software, including: Shopify, HubSpot, DoorDash, ServiceTitan, Rappi, Faire and Stripe.</p><p></p><p><br>
We&rsquo;ll be scaling even faster in 2026 to keep pace with our customer growth.</p><p></p><p><b><br>
Where we work</b></p><p>
Owner is a remote-first, global company headquartered in San Francisco, with a sales hub in Toronto. For a few of our roles we prioritize in-person collaboration at one of our office locations. Most of our teammates are distributed throughout the globe. Please review the role description and discuss with your recruiter for more details on location.</p><p></p><p><b><br>
Why we&rsquo;re looking for you</b></p><p>
We&rsquo;re building an effective, impactful Product Analytics function at Owner.com. As a Risk &amp; Payments Data Scientist, you will play a pivotal role in shaping the product roadmap through close collaboration with Product Managers to establish proper metrics and impact sizing. You will drive experimentation initiatives and manage the testing framework. You will be instrumental in designing and implementing KPIs for our payments product squad, identifying gaps and potential opportunities that will help grow the business. The best candidates will not just provide insights to the EPD (Engineering &amp; Product) org, but be a strategic driver, identifying gaps/opportunities in the money &amp; risk area, building internal alignment around them, and creating meaning business impact.</p><p>
We&rsquo;re migrating from Stripe Standard to Custom Connect / Adyen for Platforms, which means we&rsquo;ll own far more of the risk surface: merchant onboarding/underwriting, fraud detection, dispute mitigation, reserves, and payout risk. As a Risk Data Scientist you will be building the models, signals, and decisioning that protect our merchants and our P&amp;L&mdash;while keeping conversion high and friction low.</p><p></p><p><br>
For this particular role we are focused on candidates located in the San Francisco Bay Area. We are a remote-first company with a home base in SF, where our team comes together for periodic in-person collaboration (most local teammates opt to come in on Tuesdays/Thursdays). For more details chat with your recruiter!</p><p></p><p><b>
The impact you will have</b></p><p></p><ul><li><p>
Payments modeling:</p></li><li><p>
Cut losses without killing conversion: Ship ML models that reduce fraud/chargebacks and credit losses while maintaining checkout auth rates and onboarding pass-through.</p></li><li><p>
Accelerate safe growth: Create merchant risk scores and dynamic controls (e.g., reserves/holdbacks, payout delays) that scale to 10k+ restaurants.</p></li><li><p>
Give Ops superpowers: Build signals, alerts, and tools that let our Payments Ops / Risk Ops team review what matters&mdash;and automate the rest.</p></li><li><p>
Make risk measurable: Define loss budgets and risk SLIs/SLOs; deliver dashboards that make risk tradeoffs explicit.</p></li><li><p>
Build and maintain ML models for merchant underwriting, transaction fraud, chargeback propensity, payout risk.</p></li><li><p>
Design reusable frameworks for feature generation, model training, deployment, and monitoring so we can add new models quickly without reinventing the wheel.</p></li><li><p>
Payments analytics:</p></li><li><p>
Own analytics for payments, billing, and risk features, from user checkout experience to internal financial reporting.</p></li><li><p>
Monitor and improve critical KPIs such as payment success rate, failed payment recovery, fraud rates, chargeback volume, and revenue leakage. Set up monitoring for drift, stability, and business KPIs, with automated alerts.</p></li><li><p>
Identify and size revenue &amp; risk opportunities across the payments funnel (from checkout to Stripe to invoice collection).</p></li><li><p>
Partner with Product Managers on AB tests and experiments related to payments UX, fraud flags, or risk workflows.</p></li><li><p>
Collaborate with Engineering to instrument new product features and ensure great event tracking and data integrity in payment flows.</p></li><li><p>
Enhance product planning influencing product planning through informative impact sizing, enabling more strategic decision-making.</p></li><li><p>
Improve data Integrity and quality: Collaborate with developers on database design to strengthen data integrity and quality.</p></li><li><p>
Establish a Single Source of Truth (SSOT): Work alongside Data &amp; Analytics Engineers to implement robust models in DBT and Snowflake, and design dashboards that provide a unified view of business-critical data. Integrate third-party and processor signals (Stripe Radar, Adyen RevenueProtect, device/identity data) into our models.</p></li></ul><p></p><p><b>
Who you&rsquo;ll work with</b></p><p></p><ul><li><p>
Reporting Structure: This role reports directly to our VP, Business Operations, Jonathan Shenkman.</p></li><li><p>
Technical Collaboration: You will collaborate with Analytics Engineers on all technical aspects, including data modeling, data quality, and the use of tools like DBT and Snowflake.</p></li><li><p>
Work hand-in-glove with Payments Ops &amp; Risk Lead to encode policy into models, define review queues, and reduce manual workload.</p></li><li><p>
Collaborate with Payments PM/GM on onboarding UX, step-up flows, and dispute tooling; quantify conversion vs. loss tradeoffs with clear, dollarized impact.</p></li><li><p>
Provide merchant-level insights (watchlists, risk cohorts) and playbooks (what to hold, what to terminate, what to educate).</p></li></ul><p></p><p><b>
What we're looking for</b></p><p></p><ul><li><p>
4&ndash;8+ years in applied ML or risk data science (fintech/payments, marketplace, or anti-fraud).</p></li><li><p>
Hands-on with Python, SQL, and ML libraries/frameworks; comfortable with MLflow (or equivalent), and feature stores.</p></li><li><p>
Proven track record shipping production models that materially reduced losses or improved conversion; strong offline evaluation + online experimentation skills.</p></li><li><p>
Strong understanding of MLops and experience deploying MLops systems</p></li><li><p>
Experience deploying machine learning models to an api for realtime predictions</p></li><li><p>
Experience building systems for model observability after deployment</p></li><li><p>
Deep familiarity with payments/risk concepts: KYC/KYB, underwriting, auth vs capture, chargebacks, friendly fraud, card testing, reserves, payout returns, soft/hard declines.</p></li><li><p>
Strength in feature engineering on messy, imbalanced data; rigorous cost-sensitive evaluation (ROC/PR, cost curves, business impact).</p></li><li><p>
Excellent communicator who can turn model output into clear decisions and dollarized tradeoffs.</p></li><li><p>
Strong grasp of metrics design, experimentation, and product funnel analysis.</p></li><li><p>
Ability to handle ambiguity, deep dive into financial systems, and proactively flag problems before they escalate.</p></li><li><p>
KPI Development: A proven track record of developing KPIs and metrics tailored for product squads, particularly within a startup environment.</p></li><li><p>
Data Product Expertise: Ability to build comprehensive end-to-end data products.</p></li><li><p>
Organizational Skills: Highly organized with a keen eye for precision.</p></li><li><p>
Industry Experience: Prior experience in SaaS and/or startup environments is highly preferred. Experience in the restaurant industry is an added advantage.</p></li></ul><p></p><p><b>
Pay and benefits</b></p><p></p><ul><li><p>
The estimated base salary range for this role is $200k - $240k, plus a generous equity pre-IPO equity package</p></li><li><p>
Other benefits include comprehensive health coverage, unlimited PTO - plus extra fun perks!</p></li></ul><p></p><p><b>
Notice - Employment Scams</b></p><p>
Communication from our team regarding job opportunities will only be made by an Owner team member with an @owner.com email address.</p><p>
We do not conduct interviews over email or chat platforms, and we will never ask you to provide personal or financial information such as your mailing address, social security number, credit card numbers or banking information. If you believe you are being contacted by scammer, please mark the communication as &quot;phishing&quot; or &ldquo;spam&rdquo; and do not respond.</p></div><p></p>

Staff Product Data Scientist, Risk and Payments

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