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HARVEY

<div><div><h2 class="jobSectionHeader"><b>Location</b></h2>
<p>San Francisco</p>
</div><div><h2 class="jobSectionHeader"><b>Employment Type</b></h2>
<p>Full time</p>
</div><div><h2 class="jobSectionHeader"><b>Location Type</b></h2>
<p>Hybrid</p>
</div><div><h2 class="jobSectionHeader"><b>Department</b></h2>
<p>Product</p>
</div><div><h2 class="jobSectionHeader"><b>Compensation</b></h2>
<ul><li>$155K &ndash; $260K &bull; Offers Equity &bull; Offers Bonus</li>
</ul><div><p><i>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.</i></p></div></div></div>
<br><div><h1 class="jobSectionHeader"><b>Why Harvey</b></h1>
<p>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.</p>
<p>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.</p>
<p>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.</p>
<p>At Harvey, the future of professional services is being written today &mdash; and we&rsquo;re just getting started.</p>
<p></p><h1 class="jobSectionHeader"><b>Role Overview</b></h1>
<p>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.</p>
<p>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.</p>
<p></p><h1 class="jobSectionHeader"><b>What You'll Do</b></h1>
<ul><li><p>Embed with Product and Engineering teams as a trusted analytical partner, identifying opportunities to improve user experience, adoption, retention, and business impact.</p>
</li><li><p>Define and maintain core metrics that create a shared understanding of product performance and customer value.</p>
</li><li><p>Design and evaluate experiments, including A/B tests and causal inference methods, to measure the impact of product, model, and workflow changes.</p>
</li><li><p>Analyze product usage, customer segments, and go-to-market signals to surface insights, size opportunities, and inform roadmap decisions.</p>
</li><li><p>Build dashboards, reports, and self-serve tools that help teams answer product questions with confidence.</p>
</li><li><p>Develop models, forecasts, and analytical frameworks to explain user behavior, detect anomalies, and guide prioritization.</p>
</li><li><p>Translate complex analyses into clear recommendations for technical, business, and executive audiences.</p>
</li><li><p>Partner with Engineering and Data teams to improve the infrastructure that powers analytics, experimentation, and decision-making.</p>
</li><li><p>Establish the standards, practices, and culture for Product Data Science at Harvey.</p>
</li></ul><p></p><h1 class="jobSectionHeader"><b>What You Have</b></h1>
<ul><li><p>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.</p>
</li><li><p>A strong track record of using SQL, Python, and statistical methods to answer product questions and turn analysis into product or business impact.</p>
</li><li><p>Experience defining new metrics and measurement frameworks from scratch, especially for products where usage patterns, customer value, or success criteria are still being discovered.</p>
</li><li><p>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.</p>
</li><li><p>Strong product instincts and curiosity about how users adopt, evaluate, and expand their use of AI-enabled workflows.</p>
</li><li><p>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.</p>
</li><li><p>Comfort creating structure in fast-moving, ambiguous environments and raising the quality of decision-making for the teams.</p>
</li></ul><p><b>Bonus</b></p>
<ul><li><p>Experience with AI/ML products, large language models, developer tools, enterprise software, or products used in complex professional workflows.</p>
</li><li><p>Experience as an early data science or analytics hire at a hyper-growth startup, including helping define team norms, tooling, and best practices.</p>
</li><li><p>Experience supporting enterprise or B2B products, including analysis of adoption, engagement, retention, expansion, or go-to-market motion.</p>
</li><li><p>Familiarity with modern data infrastructure and the practical tradeoffs involved in building reliable analytics in a rapidly evolving product environment.</p>
</li></ul><p></p><h1 class="jobSectionHeader"><b>Compensation</b></h1>
<p>$155,000 - $260,000</p>
<p></p><h3 class="jobSectionHeader"><b>Depending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [</b><b>here</b><b>].</b></h3>
<p></p><p>#LI-SB1</p>
<p></p><p><i>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.</i></p>
<p>We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai</p></div>

Data Scientist, Product

Data Scientist, Product Analytics

Common Sense Media

<div><p><b>Data Scientist</b></p><div></div><div><div><div><div><p><b>
Organization</b></p><p><br>
Common Sense Media</p></div><div><p><b><br>
Department</b></p><p><br>
Data</p></div><div><p><b><br>
Reports To</b></p><p><br>
Senior Director, Data &amp; Analytics</p></div><div><p><b><br>
Location</b></p><p><br>
San Francisco, CA</p></div><div><div><p><b><br>
Classification</b></p><p><b><br>
Salary Range</b></p></div><div><p><br>
Full-time, Exempt</p>
<p>$140,00&ndash;$166,250</p></div></div><br>
</div></div></div><p>
</p><p></p><p><b>POSITION OVERVIEW</b></p><p>
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.</p><p>
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.</p><p>
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.</p><p>
</p><p><b>KEY RESPONSIBILITIES</b></p><p><i>
Analytics &amp; Modeling</i></p><ul><li><p>
Conduct rigorous exploratory and descriptive analyses that establish the foundational understanding of our audiences, programs, and performance.</p></li><li><p>
Develop predictive and statistical models that support organization-wide decisions.</p></li><li><p>
Apply modern machine learning techniques to ship models and analyses that drive impact.</p></li></ul><p><i>
Experimentation &amp; Causal Inference</i></p><ul><li><p>
Design and execute A/B tests and randomized controlled trials.</p></li><li><p>
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.</p></li></ul><p><i>
Impact Measurement</i></p><ul><li><p>
Lead rigorous impact analyses and program evaluations that measure how Common Sense Media's work affects kids, families, and educators.</p></li><li><p>
Apply causal inference and evaluation methods to measure real-world outcomes.</p></li></ul><p><i>
Insights &amp; Communication</i></p><ul><li><p>
Translate findings into clear, actionable recommendations for both technical and non-technical audiences.</p></li><li><h1 class="jobSectionHeader">
Partner closely with colleagues across Common Sense Media to put data to work across the organization.</h1></li></ul><p><i><br>
Analytics Engineering</i></p><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><p><i><br>
Technical Leadership</i></p><ul><li><p>
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.</p></li><li><p>
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.</p></li></ul><p>
</p><p><b>QUALIFICATIONS</b></p><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><p>
</p><p><b>WHAT WE OFFER</b></p><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><p>
</p><p><b>ABOUT COMMON SENSE MEDIA</b></p><p>
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.</p></div><p></p>

Data Scientist

<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.
 <br/>
 <br/>
 Data Scientist, Analytics (Technical Leadership) Responsibilities:
 <br/>
 <br/>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 Minimum Qualifications:
 <br/>
 <br/>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 Preferred Qualifications:
 <br/>
 <br/>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 About Meta:
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 $210,000/year to $281,000/year + bonus + equity + benefits
 <br/>
 <br/>
 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)

Kikoff

<div>
 <strong>
  Kikoff: The Fintech Powering Financial Security at Scale
  <br/>
  <br/>
 </strong>
 Kikoff is a profitable, pre-IPO fintech company on a mission to empower everyone to achieve financial security. With record revenue growth in 2025 and a unicorn valuation, we've built a suite of products that help millions of people build credit, access liquidity, and save money.
 <br/>
 <br/>
 We're scaling fast. Join us if you want to build something meaningful and help millions of people move forward financially.
 <br/>
 <br/>
 <strong>
  Why Kikoff
  <br/>
  <br/>
 </strong>
 This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 As a Operations Data Scientist at Kikoff, you work closely with cross functional teams including Customer Operations, Product Operations, Product, Engineering, and Data Engineering to make our operations smarter, faster, and more customer-centric. Operations sits at the front line of our customer experience, and you will turn the massive amount of unstructured and structured data generated there into decisions, workflows, and tools that improve both agent and customer outcomes.
 <br/>
 <br/>
 This is a high-ownership role. We are looking for someone with an owner mindset who proactively seeks out opportunities to apply a sharper technical and analytical lens to how Ops runs. You will define your own roadmap as often as you execute against someone else's.
 <br/>
 <br/>
 <strong>
  Your Responsibilities Include
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Ops AI ownership: Own and evolve Ops AI, our AI agent that helps Ops investigate customer issues and pull accurate data. Design and iterate on the agent's harness (SQL library, memory, context, skills, tools, guardrails), continuously improve its accuracy and expand its use cases as new workflows emerge.
  </li>
  <li>
   Ops Analytics and Measurement: Use data to shape how Ops runs. Define core Ops metrics, build self-serve dashboards and turn unstructured customer data into insights, design and run experiments to turn ops insights into product changes
  </li>
  <li>
   Cross-Functional Collaboration: Partner with Product Ops, CX Ops, and Operation Agents to translate data into decisions, workflows, and tooling that improve customer and agent outcomes.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelors&rsquo; or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
  </li>
  <li>
   Expert knowledge of SQL
  </li>
  <li>
   Enthusiasm and comfort using AI tools (eg. LLMs, Claude Code) in analytics
  </li>
  <li>
   Strong verbal and written communication skills
  </li>
  <li>
   A humble collaborative can-do attitude, bias to action, and a hunger to apply a technical lens to messy, ambiguous operational problems
  </li>
  <li>
   Solid understanding of statistical analysis, experimentation design, and common ML techniques
  </li>
  <li>
   1-2 years of data science experience
   <br/>
   <br/>
  </li>
 </ul>
 Nice to Have
 <br/>
 <br/>
 <ul>
  <li>
   Enthusiasm and comfort with using AI in analytics or for fintech problems
  </li>
  <li>
   Experience with Machine Learning especially in a production environment
   <br/>
   <br/>
  </li>
 </ul>
 Base Range
 <br/>
 <br/>
 $160,000 - $260,000 USD
 <br/>
 <br/>
 Equal Employment Opportunity Statement
 <br/>
 <br/>
 Kikoff Inc. is an equal opportunity employer. We are committed to complying with all federal, state, and local laws providing equal employment opportunities and considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
 <br/>
 <br/>
 Please reference the following for more information.
</div>


Data Scientist Operations

Prolific

<div>
 <strong>
  AI Trainer &ndash; Research Scientists
  <br/>
  <br/>
 </strong>
 <em>
  <strong>
   About Prolific
   <br/>
   <br/>
  </strong>
 </em>
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 <br/>
 <br/>
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 <br/>
 <br/>
 <em>
  <strong>
   The role
   <br/>
   <br/>
  </strong>
 </em>
 We&rsquo;re looking for people with Research Scientist experience to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world&rsquo;s biggest AI labs. If you have the necessary experience, we&rsquo;ll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you&rsquo;ll be invited to join Prolific as a Domain Expert participant, where you&rsquo;ll get paid to train and evaluate powerful AI models.
 <br/>
 <br/>
 Researchers looking for your skills tend to pay up to $50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.
 <br/>
 <br/>
 <em>
  <strong>
   What you&rsquo;ll be doing in the role
   <br/>
   <br/>
  </strong>
 </em>
 Completing AI training tasks such as analyzing, editing, and writing research-focused content
 <br/>
 <br/>
 Judging the performance of AI on research design, methodology, and scientific reasoning prompts
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 <br/>
 Improving cutting-edge AI models using your experience in research and experimentation
 <br/>
 <br/>
 <em>
  <strong>
   What you&rsquo;ll bring
   <br/>
   <br/>
  </strong>
 </em>
 Experience working as a Research Scientist or in a closely related research role
 <br/>
 <br/>
 A strong understanding of scientific methodology, experimental design, and data analysis
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 <br/>
 A willingness to take our skills verification test to assess your suitability for our Domain Expert participant pool
 <br/>
 <br/>
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 <br/>
 <br/>
 A reliable and fast internet connection and access to a computer
 <br/>
 <br/>
 A Paypal account to receive payment from our clients*
 <br/>
 <br/>
 <em>
  <strong>
   Why Prolific is a great platform to join as a Domain Expert participant
   <br/>
   <br/>
  </strong>
 </em>
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 <br/>
 <br/>
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 <br/>
 <br/>
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breadth and the best of humanity.
 <br/>
 <br/>
 <ul>
  <li>
   Participants are self-employed and need to declare earnings to their respective tax authorities. Prolific has no liability for any tax obligations or reporting requirements resulting from compensation received through this platform. Each participant is solely responsible for compliance with applicable tax laws in their jurisdiction.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Links to more information on Prolific
  <br/>
  <br/>
 </strong>
 Website
 <br/>
 <br/>
 Youtube
 <br/>
 <br/>
 Privacy Statement
 <br/>
 <br/>
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.
</div>


AI Training - Research Scientist (PST)

Plaid

<div><div><h2 class="jobSectionHeader"><b>Location</b></h2>
<p>San Francisco HQ; New York City Office; Seattle Office</p>
</div><div><h2 class="jobSectionHeader"><b>Address</b></h2>
<p>1098 Harrison Street, San Francisco, California, 94103</p>
</div><div><h2 class="jobSectionHeader"><b>Employment Type</b></h2>
<p>Full time</p>
</div><div><h2 class="jobSectionHeader"><b>Location Type</b></h2>
<p>Hybrid</p>
</div><div><h2 class="jobSectionHeader"><b>Department</b></h2>
<p>All DepartmentsData</p>
</div><div><h2 class="jobSectionHeader"><b>Compensation</b></h2>
<ul><li>$211,680 &ndash; $272,160</li>
</ul><div><p>Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.</p></div></div></div>
<br><div><div><p>We believe that the way people interact with their finances will drastically improve in the next few years. We&rsquo;re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid&rsquo;s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.</p>
<p>The Data Foundation &amp; AI team sits within Plaid&rsquo;s Data organization and is responsible for building the shared machine learning and AI infrastructure that powers innovation across Plaid&rsquo;s product portfolio. The team transforms Plaid&rsquo;s unique financial network data into scalable, general-purpose representations that can be leveraged by teams throughout the company. Working across the full model lifecycle, the team develops and curates pretraining datasets, trains and evaluates foundation models, and operates production-grade serving and monitoring systems to ensure reliable, high-impact AI capabilities at scale.</p>
<p></p><p>As a Research Scientist, you will advance Plaid&rsquo;s foundation models by developing novel model architectures, pretraining objectives, and fine-tuning strategies that generalize across a broad range of financial and product applications. You will contribute to the design, development, and operation of production machine learning systems, working across the full stack from data and feature engineering to training pipelines, model serving, and monitoring. The role also involves creating comprehensive evaluation frameworks that assess model performance across diverse tasks and use cases, ensuring robust and reliable outcomes. In close partnership with product and engineering teams, you will adapt foundation models to solve specific business challenges, validate their impact through rigorous experimentation, and translate research advances into production capabilities. You will also share insights and results with both internal and external audiences, helping drive innovation and elevate the practice of machine learning and AI across Plaid.</p>
<p></p><p>Responsibilities:</p>
<ul><li><p>Building a foundation model on one of the world&rsquo;s richest financial datasets that no one else has.</p>
</li><li><p>Doing research that ships: moving from experimentation and prototypes to production systems serving real customers.</p>
</li><li><p>Working across the full ML stack, from pretraining objectives and architectures to serving infrastructure and monitoring.</p>
</li><li><p>Collaborating with a high-caliber team and seeing your work amplify the capabilities of multiple product teams.</p>
</li><li><p>Helping hundreds of millions of consumers achieve greater financial freedom through data-driven products.</p>
</li></ul><p>Qualifications:</p>
<ul><li><p>MS or PhD in ML/AI/CS/Stats/Applied Math (or closely related). PhD preferred but not required &mdash; candidates with equivalent industry research and production experience will be considered.</p>
</li></ul><ul><li><p>1-3 years of industry experience building and deploying ML models, with evidence of both research depth and production delivery</p>
</li><li><p>Strong applied ML research skills with production delivery experience</p>
</li><li><p>Depth in Transformers/LLMs, representation learning, or large-scale model training</p>
</li><li><p>Distributed training experience and strong Python + software engineering fundamentals</p>
</li><li><p>Fintech / financial data domain experience - Nice to have</p>
</li><li><p>Demonstrated ability to ship models to production (not just prototype) - Nice to have</p>
</li><li><p>External publications or open-source contributions - Nice to have</p>
</li></ul><p>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!</p>
<p>Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.</p><br>
<p></p>
<p>Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.</p>
Compensation Range: $211,680 - $272,160</div></div><p></p>

Machine Learning Engineer (Research Scientist) - DFAI

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