data scientist

Common Sense Media

<div>Data Scientist<div></div><div><div><div><div>
Organization 
Common Sense Media</div><div> 
Department 
Data</div><div> 
Reports To 
Senior Director, Data &amp; Analytics</div><div> 
Location 
San Francisco, CA</div><div><div> 
Classification 
Salary Range</div><div> 
Full-time, Exempt
$140,00&ndash;$166,250</div></div> 
</div></div></div>
POSITION OVERVIEW
Common Sense Media is seeking a Data Scientist to help build data capabilities that allows the organization to answer the questions that matter most to advancing our mission and driving impact for kids and families. This is a hands-on, full-stack individual contributor role responsible for developing pipelines, models, and analyses that turn data from across the Common Sense Media ecosystem into reliable, decision-ready insights.
The Data Scientist will develop predictive and statistical models that support organization-wide decisions, design and analyze experiments, apply causal inference methods, and lead impact analyses that measure how Common Sense Media's work affects kids, families, and educators, translating findings into clear, actionable recommendations for both technical and non-technical audiences. The Data Scientist's work will span the full range of data science at Common Sense Media, from foundational data engineering and data modeling through analytics, machine learning, experimentation, and impact analysis.
As a senior technical voice on the team, the Data Scientist will help uplevel the organization's capabilities in data science, machine learning, and generative AI, advising on methodology, helping to develop and test AI product features, and raising the technical bar within product and engineering.
KEY RESPONSIBILITIES
Analytics &amp; Modeling<ul><li>
Conduct rigorous exploratory and descriptive analyses that establish the foundational understanding of our audiences, programs, and performance.</li><li>
Develop predictive and statistical models that support organization-wide decisions.</li><li>
Apply modern machine learning techniques to ship models and analyses that drive impact.</li></ul>
Experimentation &amp; Causal Inference<ul><li>
Design and execute A/B tests and randomized controlled trials.</li><li>
Leverage rigorous quasi-experimental designs (e.g., difference-in-differences, regression discontinuity) and advanced causal inference techniques to evaluate the impact of complex product and program decisions where randomized testing is not feasible.</li></ul>
Impact Measurement<ul><li>
Lead rigorous impact analyses and program evaluations that measure how Common Sense Media's work affects kids, families, and educators.</li><li>
Apply causal inference and evaluation methods to measure real-world outcomes.</li></ul>
Insights &amp; Communication<ul><li>
Translate findings into clear, actionable recommendations for both technical and non-technical audiences.</li><li><h1 class="jobSectionHeader">
Partner closely with colleagues across Common Sense Media to put data to work across the organization.</h1></li></ul> 
Analytics Engineering<ul><li>
Own the data models that turn raw data into clean, reliable, analysis-ready data sets used across the organization.</li><li>
Work with internal teams and external partners to establish data collection approaches, integrate new data sources, and ensure that incoming data is structured and trustworthy.</li><li><h1 class="jobSectionHeader">
Build and maintain the data pipelines and transformations necessary to support modeling, reporting, and impact measurement.</h1></li></ul> 
Technical Leadership<ul><li>
Serve as a senior technical voice on the team, advising on methodology and raising the technical bar around how to use data in thoughtful decision-making.</li><li>
Help uplevel the organization's capabilities in data science, machine learning, and generative AI, supporting the development and testing of AI tools and features across the organization.</li></ul>
QUALIFICATIONS<ul><li>
8+ years of experience in applied data science, analytics, or a closely related quantitative field, with a track record of shipping models and analyses that have changed decisions.</li><li>
Strong hands-on skills in SQL and Python or R, and expert use of standard machine learning libraries.</li><li>
Experience building and maintaining production data pipelines using modern cloud data warehouses (Snowflake, BigQuery, or Redshift) and modern data stack tooling (dbt, Airflow, Fivetran, or equivalents).</li><li>
Demonstrated experience designing and analyzing experiments, including A/B tests, quasi-experiments, and causal inference methods.</li><li>
Experience leading rigorous impact or program evaluation that measures real-world outcomes.</li><li>
Experience mentoring junior data scientists.</li><li>
Excellent written and verbal communication skills, with the ability to translate technical work into clear narratives for both technical and non-technical audiences.</li><li>
Demonstrated ability to serve as a senior technical voice within an organization, raising the technical bar of teammates and helping non-technical colleagues use data and AI tools effectively in their work.</li><li><h1 class="jobSectionHeader">
Strong understanding of data governance, privacy, and responsible data and AI practices, with particular sensitivity to data involving children and families.</h1></li><li><h1 class="jobSectionHeader">
Familiarity with product analytics, CRM, and marketing platforms (Amplitude, Google Analytics, Salesforce, Braze) and their underlying data structures is a plus.</h1></li><li><h1 class="jobSectionHeader">
Experience building predictive models for subscription, retention, lifetime value, or similar member or customer lifecycle problems is a plus.</h1></li><li><h1 class="jobSectionHeader">
Experience implementing and evaluating generative AI or LLM-based solutions, including prompt engineering, fine-tuning, retrieval-augmented generation, or self-hosted models, with rigorous evaluation against human or ground-truth baselines, is a plus.</h1></li><li><h1 class="jobSectionHeader">
Experience designing AI evaluation frameworks, including human-in-the-loop evaluation, bias and fairness assessment, and ongoing monitoring of model performance, is a plus.</h1></li><li><h1 class="jobSectionHeader">
Prior experience in a mission-driven, nonprofit, education, or media organization is a plus.</h1></li></ul>
WHAT WE OFFER<ul><li>
The opportunity to really make a difference in the lives of kids and families!</li><li>
A mission-driven team with a 23-year track record of impact for families and children.</li><li>
Competitive nonprofit compensation and comprehensive benefits.</li><li>
A collaborative, flexible work environment with meaningful leadership access and visibility.</li></ul>
ABOUT COMMON SENSE MEDIA
Common Sense Media is the leading nonprofit organization dedicated to improving the lives of kids and families by providing the research-backed information, education, and independent voice they need to thrive in the age of apps, algorithms, and AI. We rate, educate, and advocate for policies to protect and prepare kids online. Our ratings, research, and resources reach more than 150 million users globally, over 1.4 million educators, and more than 100,000 schools worldwide every year. Learn more at commonsense.org.</div>

Data Scientist

Genentech

<div><div><h3 class="jobSectionHeader">The Position</h3>
NOTE: Qualified candidates for both South San Francisco, CA and Mississauga, Canada will be considered equally.
At Roche, we thrive to deliver more benefits to our patients as part of our 10-year Pharma vision. An integral part of achieving this vision is to deliver new and innovative data analytics solutions to our scientists across Pharma Technical Operations (PT). PT Digital and Operational Excellence (PTE) is the organization that catalyzes the global development and execution of PT&rsquo;s Digital and Operational Excellence strategy to enable PT to realize our performance promises. We build a strong cross-functional and inclusive community, put the power of data into the hands of our people, further develop the Lean and Digital skills across PT, and scale up our Digital and Advanced Analytics solutions, for the benefit of our colleagues and patients.
We aim to activate data citizenship and digital mind, revolutionize our FAIR data ecosystem and systems landscape, re-design excellent processes, and generate transformative insights. We collaborate closely with global functions to deliver impactful value to our patients.
<h3 class="jobSectionHeader">The Opportunity</h3>
As a Senior Data Scientist and Statistician, you will play a critical role in advancing data science and statistical solutions across PT, with a special focus on biologics development. You will collaborate with scientists, engineers, business leaders, and fellow data scientists to design experiments, analyse data, and develop tools that generate insights, improve efficiency, and accelerate drug development.
Beyond hands-on analytics, you will mentor junior colleagues, promote best practices, and lead complex projects - shaping the way data science and statistics contribute to PT&rsquo;s success.
Main Responsibilities
<ul><li>Provide statistical expertise and develop data science solutions to Pharma technical operations, including process development, analytical method development, commercial manufacturing and quality control for biologics.
</li><li>Partner with cross-functional teams to frame critical scientific and operational questions, translating business needs into analytical strategies.
</li><li>Design and oversee studies to generate high-quality data for robust statistical analysis.
</li><li>Apply advanced statistical methods, machine learning, and AI to interrogate complex datasets, driving actionable insights.
</li><li>Interpret results and clearly communicate findings, influencing strategic and operational decisions.
</li><li>Develop and maintain software tools, algorithms, and automated workflows for data integration, cleaning, and large-scale analysis across heterogeneous sources.
</li><li>Build and sustain strong collaborations with internal and external stakeholders.
</li><li>Design and deliver training in statistics and data science to upskill the organisation.
</li><li>Stay current with emerging methods, regulatory guidance, and industry trends in statistics, data science, and drug development.
</li><li>Mentor junior colleagues, guiding them in study design, statistical analysis, coding best practices, and modern data science approaches, building a collaborative and supportive learning environment.
</li></ul><h3 class="jobSectionHeader">Who you are</h3>
<ul><li>Educational Qualification: Master's or Ph.D. in Statistics, Biostatistics, data science, and relevant fields.
</li><li>Expertise and Experience: Extensive experience in designing experiments (DOE), analyzing complex datasets, combined with a deep understanding of pharmaceutical technical development, particularly biologics. Advanced proficiency in statistical methods and software (e.g., R, JMP), with a proven ability to lead DOE for process characterisation, optimisation, and validation.
</li><li>Regulatory and Collaborative Skills: Strong familiarity with regulatory guidelines (FDA, EMA), excellent collaborative skills for working in multidisciplinary teams, and outstanding communication skills for reporting and stakeholder liaison.
</li><li>Problem-Solving and Project Management: Strong analytical and problem-solving skills, ability to manage multiple projects, and high attention to detail to ensure accuracy and reliability.
</li><li>Continuous Improvement and Learning: Self-motivated, able to work independently and coaching junior colleagues in teams, keen on staying updated with new developments in statistics and data science, and passionate about continuous improvement and learning.
</li></ul>Relocation benefits are not available for this posting.
The expected salary range for this position based on the primary location of South San Francisco, CA, is $156,200 to $290,200. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
#LI-PK1
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
</div><div><h2 class="jobSectionHeader">JOB FACTS</h2>
<div><div><ul><li><h3 class="jobSectionHeader">Job Sub Category</h3>
Computational Biology
</li><li><h3 class="jobSectionHeader">Schedule</h3>
Full time
</li><li><h3 class="jobSectionHeader">Job Type</h3>
Regular
</li><li><h3 class="jobSectionHeader">Posted Date</h3>
Jun 30th 2026
</li><li><h3 class="jobSectionHeader">Job ID</h3>
202606-116612</li></ul></div></div></div></div>

Senior Data Scientist

HARVEY

<div><div><h2 class="jobSectionHeader">Location</h2>
San Francisco
</div><div><h2 class="jobSectionHeader">Employment Type</h2>
Full time
</div><div><h2 class="jobSectionHeader">Location Type</h2>
Hybrid
</div><div><h2 class="jobSectionHeader">Department</h2>
Product
</div><div><h2 class="jobSectionHeader">Compensation</h2>
<ul><li>$155K &ndash; $260K &bull; Offers Equity &bull; Offers Bonus</li>
</ul><div>Additionally, this role is eligible to participate in our equity plan and benefits program. Benefits include, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits (401k match up to 4%), and flexible PTO.</div></div></div>
 <div><h1 class="jobSectionHeader">Why Harvey</h1>
At Harvey, we&rsquo;re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we&rsquo;re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. With 1500+ customers in 60+ countries, strong product-market fit, and world-class investor support, we&rsquo;re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth &mdash; personal, professional, and financial &mdash; is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission &mdash; operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today &mdash; and we&rsquo;re just getting started.
<h1 class="jobSectionHeader">Role Overview</h1>
As a Product Data Scientist, you will be a core member of Harvey's product development organization and one of the foundational members of the Data Science function. You will partner with Product, Engineering, Design, Go-to-Market, and company leadership to define how we measure product success, understand user behavior, and make high-quality decisions in a fast-moving environment.
This role is both strategic and hands-on. You will define north-star and product-level metrics, design experiments and causal analyses, build source-of-truth reporting, and turn ambiguous product questions into clear recommendations. You should be comfortable operating where the data is imperfect, the product is evolving quickly, and the right answer requires both analytical rigor and strong product judgment.
<h1 class="jobSectionHeader">What You'll Do</h1>
<ul><li>Embed with Product and Engineering teams as a trusted analytical partner, identifying opportunities to improve user experience, adoption, retention, and business impact.
</li><li>Define and maintain core metrics that create a shared understanding of product performance and customer value.
</li><li>Design and evaluate experiments, including A/B tests and causal inference methods, to measure the impact of product, model, and workflow changes.
</li><li>Analyze product usage, customer segments, and go-to-market signals to surface insights, size opportunities, and inform roadmap decisions.
</li><li>Build dashboards, reports, and self-serve tools that help teams answer product questions with confidence.
</li><li>Develop models, forecasts, and analytical frameworks to explain user behavior, detect anomalies, and guide prioritization.
</li><li>Translate complex analyses into clear recommendations for technical, business, and executive audiences.
</li><li>Partner with Engineering and Data teams to improve the infrastructure that powers analytics, experimentation, and decision-making.
</li><li>Establish the standards, practices, and culture for Product Data Science at Harvey.
</li></ul><h1 class="jobSectionHeader">What You Have</h1>
<ul><li>5+ years of experience in data science, product analytics, economics, statistics, or another quantitative field, ideally in a high-growth product company, AI company, research organization, or similarly ambiguous environment.
</li><li>A strong track record of using SQL, Python, and statistical methods to answer product questions and turn analysis into product or business impact.
</li><li>Experience defining new metrics and measurement frameworks from scratch, especially for products where usage patterns, customer value, or success criteria are still being discovered.
</li><li>Deep fluency in experimentation, causal inference, A/B testing, and statistical modeling, with good judgment about when precision matters and when directional clarity is enough.
</li><li>Strong product instincts and curiosity about how users adopt, evaluate, and expand their use of AI-enabled workflows.
</li><li>Excellent written and verbal communication skills, including the ability to influence Product, Engineering, Go-to-Market, and executive stakeholders through clear reasoning and compelling data stories.
</li><li>Comfort creating structure in fast-moving, ambiguous environments and raising the quality of decision-making for the teams.
</li></ul>Bonus
<ul><li>Experience with AI/ML products, large language models, developer tools, enterprise software, or products used in complex professional workflows.
</li><li>Experience as an early data science or analytics hire at a hyper-growth startup, including helping define team norms, tooling, and best practices.
</li><li>Experience supporting enterprise or B2B products, including analysis of adoption, engagement, retention, expansion, or go-to-market motion.
</li><li>Familiarity with modern data infrastructure and the practical tradeoffs involved in building reliable analytics in a rapidly evolving product environment.
</li></ul><h1 class="jobSectionHeader">Compensation</h1>
$155,000 - $260,000
<h3 class="jobSectionHeader">Depending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [here].</h3>
#LI-SB1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai</div>

Data Scientist, Product

Data Scientist, Product Analytics

<div>
 We are seeking experienced Data Scientists to join our team and drive impact across various product areas. As a Data Scientist, you will collaborate with cross-functional partners to identify and solve complex problems using data and analysis. Your role will involve shaping product development, quantifying new opportunities, and ensuring products bring value to users and the company. You will guide teams using data-driven insights, develop hypotheses, and employ rigorous analytical approaches to test them. You will tell data-driven stories, present clear insights, and build credibility with stakeholders. By joining our team, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
 
 
 Data Scientist, Analytics (Technical Leadership) Responsibilities:
 
 
 <ul>
 <li>
 Work with complex data sets to solve challenging problems using analytical and statistical approaches
 </li>
 <li>
 Apply technical expertise in quantitative analysis, experimentation, and data mining to develop product strategies
 </li>
 <li>
 Identify and measure success through goal setting, forecasting, and monitoring key metrics
 </li>
 <li>
 Partner with cross-functional teams to inform and execute product strategy and investment decisions
 </li>
 <li>
 Build long-term vision and strategy for programs and products
 </li>
 <li>
 Collaborate with executives to define and develop data platforms and instrumentation
 </li>
 <li>
 Effectively communicate insights and recommendations to stakeholders
 </li>
 <li>
 Define success metrics, forecast changes, and set team goals
 </li>
 <li>
 Support developing roadmaps and coordinate analytics efforts across teams
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 </li>
 <li>
 Mathematics, Statistics, Operations Research) 5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab)
 </li>
 <li>
 8+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
 </li>
 <li>
 Experience working effectively with and leading complex analytics projects across multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
 </li>
 <li>
 Experience with predictive modeling, machine learning, and experimentation/causal inference methods
 </li>
 <li>
 Experience communicating complex technical topics in a clear, precise, and actionable manner
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <ul>
 <li>
 10+ years of experience communicating the results of analyses to leadership teams to influence the strategy
 </li>
 <li>
 Masters or Ph.D. Degree in a quantitative field
 </li>
 <li>
 Bachelor's Degree in an analytical or scientific field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research)
 </li>
 <li>
 10+ years of experience doing complex quantitative analysis in product analytics
 </li>
 <li>
 Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
 </li>
 <li>
 Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
 </li>
 <li>
 Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
 
 
 </li>
 </ul>
 About Meta:
 
 
 Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today&mdash;beyond the constraints of screens, the limits of distance, and even the rules of physics.
 
 
 Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
 
 
 Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
 
 
 $210,000/year to $281,000/year + bonus + equity + benefits
 
 
 Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
</div>

Data Scientist, Analytics (Technical Leadership)

Pinterest

<div><div>About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.</div>
What you'll do:
<ul>
<li>Be the technical lead for the forecasting team. Own the strategy and implementation of forecasting models of key company metrics (e.g., monthly active users), delivering accurate, interpretable forecasts at scale.</li>
<li>Lead the full modeling lifecycle end to end: problem framing, feature engineering, model development and prototyping, experimentation and backtesting, deployment, monitoring/drift detection, and explainability.</li>
<li>Set the forecasting technical vision. Define model architectures and standards, and partner with Engineering to shape the forecasting platform for efficient training/inference today and the scalability needed for the next generation of models.</li>
<li>Translate forecasts into decisions. Present outputs, scenario analyses, and recommendation frameworks to senior leadership with clarity and brevity. This is a high‑visibility role with regular VP-level exposure.</li>
<li>Drive broader time‑series impact beyond point forecasts&mdash;e.g., anomaly detection, automated root‑cause analysis, campaign/channel attribution, and early‑warning signals for business health.</li>
<li>Embed forecasting into the business. Partner with BizOps/Finance and product teams to integrate forecasts and insights into operational rhythms, executive decision-making, and strategic planning.</li>
<li>Lead and mentor. Guide the work of at least two data scientists, raising the bar on technical quality, execution, and impact through candid, continuous feedback and coaching.</li></ul> 


What we're looking for:
<ul>
<li>8+ years of combined post-graduate academic and industry experience building and shipping production time‑series/forecasting models with web‑scale data.</li>
<li>Bachelor's degree in a relevant field such as Computer Science or equivalent experience.</li>
<li>A track record of delivering adjustable, well‑calibrated, and explainable forecasting systems that informing decision-making.</li>
<li>Strong background in time‑series modeling and applied statistics/econometrics; advanced degree (MS or PhD) preferred.</li>
<li>Expertise in at least one scripting language (ideally Python).</li>
<li>Strong SQL skills (Hive/Presto/Spark SQL) and experience building reliable data pipelines/workflows (e.g., Airflow).</li>
<li>Business acumen and ownership mindset&mdash;able to simplify complex problems, connect model outputs to business levers, and prioritize for impact.</li>
<li>Excellent communication skills&mdash;able to distill complex analyses and uncertainty into concise narratives for executive audiences.</li>
<li>Proven technical leadership&mdash;success leading critical projects and materially influencing the scope and output of other contributors.</li></ul> 


Relocation Statement:
<ul>
<li>This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.</li></ul> 


In-Office Requirement Statement:
<ul>
<li>We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.</li>
<li>This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.</li></ul> 


#LI-NM4

#LI-REMOTE<div>
Our Commitment to Inclusion:
<div>
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.</div>
<div></div>
<div>By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.</div></div></div>

Staff Data Scientist, Forecasting

Salesforce

<div>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Software Engineering
Job Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
Lead member of technical staff - Machine Learning Engineering
Job Category: Software Engineering
Job Details
About Salesforce
We&rsquo;re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too &mdash; driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good &ndash; you&rsquo;ve come to the right place.
We are a foundation machine learning platform team within the Trust Intelligence Platform organization with a main focus to build and accelerate scalable and resilient machine learning pipelines across the security engineering organization.
We are looking for a highly motivated, hands-on lead machine learning engineer with a strong business understanding of cybersecurity problems, who acts as a force multiplier security data scientist for our security organization. The lead will not simply build models; they will architect the data-driven strategy for our threat detection capabilities.
Your impact:
<ul><li>Shape the Defense Strategy: You will own the decision-making process&mdash;translating vague security threats into concrete mathematical problems. By championing a rapid prototyping culture, you will validate hypotheses in days rather than months, ensuring our engineering resources are focused only on high-value detections while killing low-signal ideas early.
</li><li>Detect the &quot;Unknown Unknowns&quot;: You will lead the evolution of our threat detection, introducing more advanced probabilistic modeling, graph analytics, supervised and unsupervised learing. Your work will expose sophisticated threats&mdash;such as active system intrusions, lateral movement, beaconing, and insider attacks&mdash;that evade traditional defenses, directly reducing the organization's risk surface.
</li><li>Elevate the Organization: You will act as a force multiplier, mentoring junior scientists and engineers, and building the internal tooling, feature stores, and libraries that make the whole team faster. You will influence the broader security engineering roadmap to ensure a closed loop security telemetry that is treated as a first-class citizen.
</li><li>Operationalize Intelligence: By prioritizing engineering rigor (CI/CD, scalable code) and adversarial resilience, you will deliver production-grade models that the SOC actually trusts&mdash;minimizing &quot;alert fatigue&quot; and maximizing analyst efficiency.
</li></ul>Required skills:
<ul><li>Extensive experience (3-5+ years) in data science, with at least 2+ years dedicated to the cybersecurity domain designing, implementing and deploying systems of anomaly detection, clustering, and graph models in production.
</li><li>Hands-on comfort with high-volume logs and proficiency with Spark/Pyspark, Snowflake, Flink and streaming services such as Apache Kafka
</li><li>Deep understanding and application of containerization (Docker) and workflow orchestration (Kubernetes, Apache Airflow) for automated ML pipelines.
</li><li>Mastery of Python programming, including proficiency in leading ML frameworks (TensorFlow, PyTorch) and adherence to software engineering best practices.
</li><li>Demonstrated success in implementing comprehensive MLOps methodologies, encompassing CI/CD pipelines, testing protocols, and model performance monitoring.
</li><li>Solid foundation in feature engineering techniques and the implementation of feature stores.
</li><li>Experience in formulating ML governance policies and ensuring adherence to data security regulations.
</li><li>Ability to explain complex statistical concepts to non-technical stakeholders and executive leadership.
</li><li>Proven ability to manage scope, timelines, and stakeholder expectations across multiple organizations.
</li><li>High degree of autonomy with the ability to look at a vague business problem and structure a data-driven solution without needing a predefined roadmap.
</li></ul>Preferred skills:
<ul><li>Masters or PhD in a quantitative field
</li><li>Expertise in advanced Natural Language Processing (NLP) methodologies.
</li><li>Experience contributing to open-source security data science tools.
</li><li>Presentations at major security conferences (Black Hat, DEF CON, BSides) or data conferences.
</li><li>Background in offensive security (Penetration Testing/Red Teaming) with an &quot;attacker's mindset.&quot;
</li><li>Demonstrated experience conducting research or working collaboratively with Machine Learning (ML) research teams.
</li><li>Previous experience in a mentoring role for junior engineers.
</li><li>Track record of publications and/or patents in quantitative disciplines.
</li></ul>Unleash Your Potential
When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates&rsquo; resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.&amp;#xa;&amp;#xa;The typical base salary range for this position is $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.&amp;#xa;&amp;#xa;The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.</div>

Lead Machine Learning Engineer - LMTS

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