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associate machine learning engineer

data engineer

HappyRobot

<div>
 
 About HappyRobot
 
 
 
 HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate - they make decisions, take action, and run operations autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by a16z and Base10 with over $60M raised, we power critical operations for global enterprises worldwide.
 
 
 Our platform is battle-tested in the most demanding environments - where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto.
 
 
 
 About The Role
 
 
 
 <ul>
 <li>
 Build foundational data products, dashboards and tools to enable self-serve analytics to scale across the company.
 </li>
 <li>
 Develop insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company.
 </li>
 <li>
 Build and maintain robust data pipelines and models to ensure data quality.
 </li>
 <li>
 Partner with Product, Engineering, and Design teams to inform decisions.
 </li>
 <li>
 Translate complex data into clear, actionable insights for product teams.
 </li>
 <li>
 Love working with data. Love making product better. Love finding the story behind the numbers.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Define, build, and maintain product metrics, dashboards, and pipelines.
 </li>
 <li>
 Write SQL and Python code to extract, transform, and analyze data.
 </li>
 <li>
 Design and run experiments (A/B tests) to support product development.
 </li>
 <li>
 Proactively explore data to identify product opportunities and insights.
 </li>
 <li>
 Collaborate with cross-functional teams to ensure data-driven decisions.
 </li>
 <li>
 Ensure data quality, reliability, and documentation across analytics efforts.
 
 
 </li>
 </ul>
 
 Must Have
 
 
 
 <ul>
 <li>
 3+ years of experience as an Analytics Data Engineer or similar Data Science &amp; Analytics roles.
 </li>
 <li>
 Strong SQL and data engineering skills to transform data into accurate, clean data models (e.g., dbt, Airflow, data warehouses).
 </li>
 <li>
 Proficiency in Python for data analysis and modeling.
 </li>
 <li>
 Excellent communication skills: able to explain complex data insights clearly.
 </li>
 <li>
 Curious, collaborative, and driven to make an impact in a fast-paced environment.
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience in B2B SaaS or AI/ML products.
 </li>
 <li>
 Familiarity with product analytics tools (e.g., Mixpanel, Amplitude).
 </li>
 <li>
 Exposure to machine learning concepts or AI-powered systems.
 
 
 </li>
 </ul>
 
 Why join us?
 
 
 
 <ul>
 <li>
 Opportunity to work at a high-growth AI startup, backed by top investors.
 </li>
 <li>
 Rapidly growing and backed by top investors including a16z, Y Combinator, and Base10.
 </li>
 <li>
 Ownership &amp; Autonomy - Take full ownership of projects and ship fast.
 </li>
 <li>
 Top-Tier Compensation - Competitive salary + equity in a high-growth startup.
 </li>
 <li>
 Comprehensive Benefits - Healthcare, dental, vision coverage.
 </li>
 <li>
 Work With the Best - Join a world-class team of engineers and builders.
 
 
 </li>
 </ul>
 
 Our Operating Principles
 
 
 
 
 
 Extreme Ownership
 
 
 
 
 We take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting &mdash; if something needs fixing, we own it and make it better. This means stepping up, even when it&rsquo;s not &ldquo;your job.&rdquo; If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We don&rsquo;t wait for someone else to solve it &mdash; we lead with accountability and expect the same from those around us.
 
 
 
 
 Craftsmanship
 
 
 
 
 Putting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for &ldquo;just fine.&rdquo; We sweat the details because details compound. Whether it&rsquo;s a product feature, an internal doc, or a sales call &mdash; we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build &mdash; even when nobody&rsquo;s watching.
 
 
 
 
 We are &ldquo;majos&rdquo;
 
 
 
 
 Be friendly &amp; have fun with your coworkers. Always be genuine &amp; honest, but kind. &ldquo;Majo&rdquo; is our way of saying: be a good human. Be approachable, helpful, and warm. We&rsquo;re building something ambitious, and it&rsquo;s easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego.
 
 
 
 
 Urgency with Focus
 
 
 
 
 Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. We&rsquo;re running a high-speed marathon &mdash; not a sprint with no strategy.
 
 
 
 
 Talent Density and Meritocracy
 
 
 
 
 Hire only people who can raise the average; &lsquo;exceptional performance is the passing grade.&rsquo; Ability trumps seniority. We believe the best teams are built on talent density &mdash; every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players &mdash; that&rsquo;s how we win.
 
 
 
 
 First-Principles Thinking
 
 
 
 
 Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We don&rsquo;t copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. It&rsquo;s how we build what others think is impossible.
 
 
 
 The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller.
 
 
 
 
 By sending us your CV, you consent to the processing of your personal data for the purpose of evaluating and selecting you as a candidate for the position. Your personal data will be treated confidentially and will only be used for the recruitment process of the selected job offer.
 
 
 
 
 In relation to the period of conservation of your personal data, these will be eliminated after three months of inactivity in compliance with the GDPR and legislation on the protection of personal data.
 
 
 
 
 If you wish to exercise your rights of access, rectification, deletion, portability or opposition in relation to your personal data, you can do so through security@happyrobot.ai subject to the GDPR.
 
 
 
 
 For more information, visit
 
 
 https://www.happyrobot.ai/privacy-policy
 
 
 
 
 By submitting your request, you confirm that you have read and understood this clause and that you agree to the processing of your personal data as described.
 
</div>

Data Engineer

Embedding VC

<div><h3 class="jobSectionHeader">About OpenArt</h3>
OpenArt is an AI Storytelling and Visual Creation Platform used by millions worldwide. We&rsquo;re building the next generation of creative tools powered by cutting-edge AI, enabling anyone to create videos, visuals, characters, and stories with unprecedented speed and imagination. We believe the future of creativity is AI-native, and we&rsquo;re shaping that future.<h3 class="jobSectionHeader">
Why Join OpenArt</h3><ul><li>
Own the measurement and attribution layer of a fast-scaling AI company.</li><li>
Direct impact on growth &mdash; your work drives acquisition efficiency and revenue.</li><li>
Work across product, marketing, and data &mdash; highly cross-functional role.</li><li>
Build from 0 1 &mdash; define how we track, attribute, and optimize growth.
High ownership, low process, fast iteration environment.</li><li>
7&ndash;10X revenue growth over the past 2 years &mdash; now scaling growth infrastructure.</li></ul><h3 class="jobSectionHeader">
About the Role</h3>
We&rsquo;re looking for a Growth Data Engineer to build and own OpenArt&rsquo;s marketing data and attribution systems, ensuring that all acquisition and lifecycle efforts are accurately measured and optimized.
This role sits at the intersection of data engineering, marketing tech, and analytics &mdash; focused on making sure that data flows reliably between product, warehouse, CRM, and ad platforms.
You will be responsible for ensuring that every marketing dollar is measurable, attributable, and optimizable &mdash; from first touch to revenue.<h3 class="jobSectionHeader">
What You&rsquo;ll Do</h3><ul><li>
Build and maintain marketing attribution systems (UTM tracking, user journey, conversion mapping)</li><li>
Implement and manage 1st-party data passback to ad platforms (e.g., conversions, revenue, LTV signals)</li><li>
Configure and maintain tracking infrastructure:<ul><li>
GTM (client + server-side)</li><li>
Google Ads (Enhanced Conversions)</li><li>
Meta Pixel + Conversions API</li><li>
LinkedIn, TikTok, and other ad platforms</li></ul></li><li>
Set up and maintain conversion events and schemas across platforms</li><li>
Ensure consistent event definitions and naming across product, CRM, and ad platforms</li><li>
Build and manage audience sync pipelines</li><li>
Integrate CRM and warehouse data into ad platforms for optimization (offline conversions, lead stages, revenue)</li><li>
Operationalize new marketing experiments (UTMs, tracking parameters, campaign setup)</li><li>
Debug and resolve tracking and attribution discrepancies across systems (e.g., Ads vs CRM vs warehouse)</li><li>
Build and validate marketing and pipeline dashboards, ensuring data accuracy and consistency</li><li>
Implement privacy-safe tracking practices (Consent Mode, CMP integrations)</li><li>
Partner closely with growth, product, and data teams to ensure measurement supports decision-making</li></ul><h3 class="jobSectionHeader">
What We&rsquo;re Looking For</h3>
Core Requirements<ul><li>
3&ndash;5 years of experience in growth data, marketing data engineering, or analytics engineering</li><li>
Strong hands-on experience with:<ul><li>
GTM, pixels, conversion APIs</li><li>
Ad platforms (Google Ads, Meta, etc.)</li></ul></li><li>
Experience implementing conversion tracking and attribution systems</li><li>
Experience sending offline conversions / LTV signals back to ad platforms</li><li>
Familiarity with data pipelines and warehouse concepts (BigQuery, SQL, ETL/ELT)</li><li>
Strong SQL skills; comfortable working with data directly</li><li>
Strong debugging skills &mdash; able to systematically investigate and resolve data discrepancies</li><li>
Comfortable working cross-functionally with marketing, product, and data teams</li><li>
High ownership, fast execution, and strong attention to detail</li></ul>
Nice to Have<ul><li>
Experience supporting performance marketing teams</li><li>
Familiarity with:<ul><li>
Attribution models (last-click, MTA, probabilistic vs deterministic)</li><li>
Privacy frameworks (SKAN, ATT, Privacy Sandbox)</li></ul></li><li>
Experience with mobile attribution tools (AppsFlyer, Adjust, Branch)</li><li>
Experience with experimentation and A/B testing frameworks</li><li>
Experience in consumer product, marketplaces, or e-commerce</li><li>
Basic Python or scripting for automation</li></ul><h3 class="jobSectionHeader">
Tech Stack You&rsquo;ll Work With</h3>
GTM, Google Ads, Meta Ads, TikTok Ads, BigQuery, Metabase, Amplitude, Stripe, SQL, GCP<h3 class="jobSectionHeader">
Compensation</h3><ul><li>
Competitive base salary and bonus program</li><li>
Equity &mdash; meaningful ownership in what you build</li><li>
High autonomy, high growth environment</li></ul><h3 class="jobSectionHeader">
Work Setup</h3><ul><li>
Bay Area preferred (hybrid allowed)</li><li>
Visa sponsorship available</li><li>
We&rsquo;ll consider remote</li></ul></div>

Growth Data Engineer

Data Engineer, Analytics (Technical Leadership)

Uber

<div>
 
 About The Role
 
 
 
 The Growth and Marketing Platform Data Team is looking for a highly skilled and passionate Data Engineer to build and scale Uber's data infrastructure. In this role, you'll develop high-performance data pipelines, real-time streaming systems, and robust data architectures that power Uber's growth and marketing initiatives.
 
 
 You'll collaborate with Product Managers, Data Scientists, Data Platform Engineers, and Marketing Operations to design scalable, efficient, and reliable data solutions that drive business impact. This is a highly visible and impactful role for someone who thrives on data at scale, technical leadership, and solving ambiguous problems with clarity and precision.
 
 
 
 What You Will Do
 
 
 
 <ul>
 <li>
 Design, develop, and maintain scalable data pipelines and backend services for processing large-scale web event analytics.
 </li>
 <li>
 Lead the development of core data infrastructure, ensuring high availability, performance, and reliability.
 </li>
 <li>
 Solve complex challenges at the intersection of low latency, high correctness, and full determinism.
 </li>
 <li>
 Architect and optimize data models, ETL/ELT workflows, and distributed data processing frameworks.
 </li>
 <li>
 Participate in code reviews, mentor junior engineers, and enforce best practices in data engineering.
 </li>
 <li>
 Diagnose and resolve data quality issues, ensuring accuracy, efficiency, and security.
 
 
 </li>
 </ul>
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 4+ years of experience in data engineering or backend software development.
 </li>
 <li>
 Proficiency in Python, SQL, Java, or Scala for data pipeline development.
 </li>
 <li>
 Proficiency in Big Data frameworks (e.g., Spark, Flink, Presto, MapReduce) and distributed computing.
 </li>
 <li>
 Data warehouse and Data Modeling experience
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in Web and SEO Analytics
 </li>
 <li>
 Experience in Marketing Technologies
 </li>
 <li>
 Designing and executing on Real-time and Near Real-time Systems
 
 
 </li>
 </ul>
 For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 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., For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 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>

Data Engineer - Growth and Marketing Platform

Chime

<div>
 
 About The Role
 
 
 
 Chime&rsquo;s Growth Engineering team is focused on building product experiences that directly move business metrics and help millions of people achieve financial progress. Within Growth, the Paid Ads &amp; Acquisition Engineering team owns the systems that power user acquisition at scale - from marketing data pipelines to attribution and spend optimization. You&rsquo;ll directly influence how Chime deploys and optimizes hundreds of millions in paid media spend.
 
 
 As a Growth Engineer on this team, you will work at the intersection of product, data, and marketing. You&rsquo;ll build and maintain data-intensive systems that enable efficient paid acquisition, power experimentation, and unlock new growth channels such as partnerships and incentives. This role is well-suited for engineers who enjoy working with data pipelines, distributed systems, and ambiguous problem spaces where measurement and iteration are critical.
 
 
 The base salary offered for this role and level of experience will begin at $133,000 and up to $184,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.
 
 
 
 In This Role, You Can Expect To
 
 
 
 <ul>
 <li>
 Build and scale backend services, data pipelines, and APIs that power Chime&rsquo;s paid acquisition and marketing systems
 </li>
 <li>
 Develop and maintain integrations with major ad platforms (Meta, Google, TikTok, Affiliate etc), including conversion APIs, reverse ETL pipelines, Airflow workflows, and data integrations that enable campaign execution and measurement
 </li>
 <li>
 Partner closely with marketing, data science, analytics, and product teams to improve acquisition efficiency and performance
 </li>
 <li>
 Design measurement systems for LTV/CAC, attribution, and incrementality
 </li>
 <li>
 Support and evolve incentive and partnership platforms that drive new user acquisition channels
 </li>
 <li>
 Rapidly prototype and iterate on experiments that improve conversion, CAC efficiency, and downstream user quality
 </li>
 <li>
 Analyze system and campaign performance post-launch to inform optimizations and strategy
 </li>
 <li>
 Improve reliability, scalability, and observability of data and backend systems
 </li>
 <li>
 Contribute to a culture of technical excellence through code reviews, mentorship, and best practices
 
 
 </li>
 </ul>
 
 To Thrive In This Role, You Have
 
 
 
 <ul>
 <li>
 3+ years of experience building scalable software or data systems in production environments
 </li>
 <li>
 Experience with backend development (Ruby on Rails, Golang, or similar) and/or data infrastructure
 </li>
 <li>
 Familiarity with data pipelines, orchestration tools (e.g. Airflow), and modern data stacks
 </li>
 <li>
 Experience designing APIs and working with databases, event streams, or data warehouses
 </li>
 <li>
 Interest in or exposure to marketing systems such as attribution, paid ads platforms, or growth analytics
 </li>
 <li>
 A strong product and metrics mindset, with a focus on experimentation and measurable impact
 </li>
 <li>
 Comfort working across the stack and navigating ambiguity in fast-moving environments
 </li>
 <li>
 Strong collaboration and communication skills with cross-functional partners
 
 
 </li>
 </ul>
 
 Bonus
 
 
 
 <ul>
 <li>
 Experience with reverse ETL tools such as Hightouch
 </li>
 <li>
 Background in growth engineering, paid acquisition, or marketing tech (MarTech) systems
 </li>
 <li>
 Experience with attribution modeling, incrementality testing, or spend optimization systems
 </li>
 <li>
 Exposure to incentive platforms or partnership integrations
 
 
 </li>
 </ul>
 
 A Little About Us
 
 
 
 At Chime, we believe that everyone can achieve financial progress. We created Chime&mdash;a financial technology company, not a bank*&mdash;on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential.
 
 
 We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members.
 
 
 We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress.
 
 
 We know that to achieve our mission, we must earn and keep people's trust&mdash;so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall&mdash;our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential.
 
 
 Because if we don't&mdash;who will?
 
 
 <ul>
 <li>
 Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC.
 
 
 </li>
 </ul>
 
 What We Offer For Our Full-time, Regular Employees
 
 
 
 <ul>
 <li>
 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. Whether you&rsquo;re coming in regularly or are part of our fully remote program, you&rsquo;ll stay engaged with your work and teammates.
 </li>
 <li>
 💻 In-office perks including backup child, elder, and/or pet care, plus a subsidized commuter benefit to support your regular commute
 </li>
 <li>
 💰 Competitive salary based on experience
 </li>
 <li>
 ✨ 401k match plus great medical, dental, vision, life, and disability benefits
 </li>
 <li>
 🏝 Generous vacation policy and company-wide Chime Days, bonus company-wide paid days off
 </li>
 <li>
 🫂 1% of your time off to support local community organizations of your choice
 </li>
 <li>
 👟 Annual wellness stipend to use towards eligible wellness related expenses
 </li>
 <li>
 👶 Up to 24 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents
 </li>
 <li>
 👪 Access to Maven, a family planning tool, with $15k lifetime reimbursement for egg freezing, fertility treatments, adoption, and more.
 </li>
 <li>
 🎉 In-person and virtual events to connect with your fellow Chimers&mdash;think cooking classes, guided meditations, music festivals, mixology classes, paint nights, etc., and delicious snack boxes, too!
 </li>
 <li>
 💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress
 
 
 </li>
 </ul>
 We know that great work can&rsquo;t be done without a diverse team and inclusive environment. That&rsquo;s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals.
 
 
 Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: benefits@chime.com.
 
 
 To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice.
</div>

Software Engineer, Growth - Paid Ads & Acquisition

SoFi

<div><div>Employee Applicant Privacy Notice

Who we are:
<div>
Shape a brighter financial future with us.

Together with our members, we're changing the way people think about and interact with personal finance.

We're a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we're at the forefront. We're proud to come to work every day knowing that what we do has a direct impact on people's lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
</div></div>
The Role 
The Risk Data Science team is seeking a strategic and technically deep Machine Learning Engineer to lead the evolution of SoFi's Home Loan and Home Equity risk frameworks. This role is at the center of a high-priority initiative to deliver a comprehensive, loan-level credit risk and valuation framework for our home lending portfolios.

As a key technical leader, you will apply state-of-the-art ML methodologies to solve complex problems&mdash;including default and prepayment modeling, property valuation (AVMs), and credit risk assessment&mdash;ensuring our high-value secured loan products are backed by world-class data science.

What You'll Do
<ul>
<li>Lead the design and implementation of ML models for mortgage-specific use cases, including credit underwriting, debt-to-income (DTI) validation, and automated appraisal reviews.</li>
<li>Provide technical oversight and end-to-end ownership of externally developed models, ensuring they meet rigorous internal standards for quality, performance, and scalability.</li>
<li>Present model performance and portfolio insights to senior leadership, translating complex data into actionable credit and business strategies.</li>
<li>Collaborate with Model Risk Management (MRM) and governance teams to ensure all models are developed with the technical rigor required to satisfy complex regulatory and compliance standards.</li>
<li>Partner with Product and Engineering teams to operationalize models, overseeing deployment, real-time monitoring, and seamless integration into core business systems.</li>
<li>Continuously explore and leverage in-house, external, and open-source ML frameworks to build the next generation of proprietary mortgage risk tools.</li></ul> 


What You'll Need
<ul>
<li>Master's degree in Computer Science, Statistics, Mathematics, Physics, Engineering, or a quantitative field required. Ph.D. preferred.</li>
<li>5+ years of direct experience with building, implementing, and deploying machine learning models within Home Loans or Home Equity lending environments.</li>
<li>Expert knowledge of statistical modeling and ML methods, including linear/logistic regression, ensemble methods (XGBoost/LightGBM), clustering, and outlier detection.</li>
<li>Strong programming skills in Python and SQL.</li>
<li>Hands-on experience with ML model implementation in production environments using tools such as AWS SageMaker, Git, Docker, and CI/CD pipelines.</li>
<li>Strong ability to distill complex technical methodologies into simple, persuasive terms for non-technical stakeholders.</li></ul> 


Nice To Have
<ul>
<li>Proven track record in technical model documentation and navigating the Model Risk Management lifecycle.</li>
<li>Experience working in a cross-functional capacity across Product, Engineering, and Risk departments.</li>
</ul><div><div>Compensation and Benefits</div>
<div>The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate's experience, skills, and location.</div>
<div></div>
<div>To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!</div>
<h5 class="jobSectionHeader">SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.</h5>
<h5 class="jobSectionHeader">The Company hires the best qualified candidate for the job, without regard to protected characteristics.</h5>
<h5 class="jobSectionHeader">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</h5>
<h5 class="jobSectionHeader">New York applicants: Notice of Employee Rights</h5>
<h5 class="jobSectionHeader">SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.</h5>
<h5 class="jobSectionHeader">Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.</h5>
<div>Internal Employees</div>
<div>If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.</div></div></div>

Staff Data Scientist

Triumph

<div><h1 class="jobSectionHeader">About Us</h1>
Triumph makes mobile gaming more thrilling by letting players wager - and win - real money, play in mass multiplayer games, and compete in social tournaments. We've built the top app in our App Store category and sustained exponential month-over-month growth on our revenue and active players. We're hyper-scaling our team and continuing to innovate, launching new products like Rips, our collectibles app, which has found huge success and is continuing to expand. And we're just getting started.
Triumph is backed by some of the top consumer VCs including Goodwater Capital, General Catalyst, and DraftKings Drive Fund.<h1 class="jobSectionHeader">
The Role</h1>
As a Data Scientist, you'll own the quantitative systems that drive how millions of real-money players experience Triumph's products, from their first session to long-term retention and monetization. You'll build the models and frameworks behind our most critical business decisions: how we price, how we pay out, how we match players, and how we grow.
You'd be joining a small, high-output quant team (4 people today) that operates like a trading desk. We build the mathematical systems that power Triumph's core business: pricing engines, payout distributions, matchmaking algorithms, risk models, and player behavior systems. Every model we ship touches real money and real users. You see the impact in the numbers the next day.<h1 class="jobSectionHeader">
What You'll Do</h1><ul><li>
Monetization &amp; Pricing: Develop and optimize the pricing engines, payout structures, and edge calculations that are the mathematical backbone of Triumph's revenue. Own pack economics, rarity calibration, and pricing models for Rips by Triumph.</li><li>
User Journey &amp; Retention: Build models that map the full player lifecycle: acquisition, activation, engagement, monetization, churn risk. Identify the quantitative levers that move retention and LTV, and design interventions that act on them.</li><li>
Experimentation: Design and analyze experiments (A/B tests and beyond) with rigorous statistical methodology. Own the measurement framework that tells us what's actually working across the product.</li><li>
Behavioral Modeling: Develop ML and statistical models on rich, high-frequency user behavior data (session patterns, spend curves, matchmaking outcomes, gameplay trajectories) to drive both product decisions and real-time production systems.</li><li>
Growth &amp; Acquisition: Build models that directly inform acquisition spend and channel optimization, connecting upstream marketing decisions to downstream LTV and monetization outcomes.</li><li>
Cross-Functional Impact: Partner closely with engineering, product, and leadership to translate model outputs into shipped features and strategic decisions. Identify high-leverage quantitative problems across the business and drive them from formulation to production impact.</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
Bachelor's degree in a quantitative subject: math, physics, computer science, statistics, economics, or a related discipline.</li><li>
True depth and mastery in at least one quantitative domain: probability, statistics, applied ML, causal inference, or mathematics. We want spiky people who are confident they are among the best in their discipline.</li><li>
Proficiency in Python and SQL.</li><li>
Experience working with large-scale user or behavioral datasets.</li></ul><h1 class="jobSectionHeader">
Preferred Qualifications</h1><ul><li>
Experience in consumer tech, gaming, fintech, or marketplace data science, particularly in monetization, LTV modeling, or experimentation.</li><li>
Prior experience as a quantitative trader or quantitative researcher.</li><li>
Experience in competitive math, physics, or CS olympiads, or a graduate degree in a quantitative discipline.</li><li>
Nationally competitive in any activity. Some members of our team include national champions in debate, Clash Royale, and Poker.</li></ul><h1 class="jobSectionHeader">
Why Triumph?</h1><ul><li>
High growth. Build a high-scale consumer platform that touches gaming, finance, and social with the autonomy to set our web direction.</li><li>
High agency. Small, high-impact engineering team that is growing rapidly with significant opportunity for leadership and growth.</li><li>
High energy. Passionate team who are proud of our work and velocity (16x year over year growth).</li><li>
Competitive salary and benefits. $400/mo lunch credit, healthcare, vision, dental, 401k, etc.</li></ul>
Our team gathers 5 days a week at Triumph&rsquo;s headquarters at Levi&rsquo;s Plaza in San Francisco.
Compensation Range: $160K - $265K</div>

Data Scientist

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