Senior Data Scientist, Generative AI

Posted 2 Days Ago
San Francisco, CA
172K-206K Annually
Senior level
Artificial Intelligence • Big Data • Machine Learning
The Data Platform for AI: High quality training and validation data for AI applications.
The Role
As a Senior Data Scientist at Scale, you will build evaluation frameworks for LLMs, adapt statistical models for complex problems, partner with stakeholders for data-driven decisions, and drive product development for generative AI applications.
Summary Generated by Built In

Scale is looking for a data scientist to join our team to help advance the development of AI. As a member of the data science team, you will lead the charge of building our data science infrastructure for Gen AI products and driving insights that lead to step-function improvements in how we operate. The ideal candidate is detail-oriented, rigorous about validating results, talented at distilling down complexity, and loves tackling and solving hard problems.

You will:

  • Build evaluation frameworks to measure LLMs efficacy, ground truth dataset quality, and guide product development roadmap
  • Adapt statistical models to solve specific hard problems in fields of economics, price theory, and marketplace experimentation
  • Be a proactive partner to your business stakeholders and provide insights and conclusions rather than just data outputs/models
  • Tackle business-critical questions by developing and testing hypotheses, and aiding evidence-based decision making
  • Partner with Product Managers, Data Engineers, Data Scientists, and Business Stakeholders to drive business decisions and product roadmaps

Ideally, You'd Have:

  • 5+ years of industry experience in a highly analytical role
  • Degree in a quantitative field (e.g., Maths, Engineering)
  • Strong proficiency in Python
  • Experience with marketplace experimentation
  • Expert-level proficiency in writing complex SQL queries across large datasets
  • Expertise in designing metrics and diagnosing data inconsistencies

Please note that in order to maintain integrity to our Scale titling philosophy, we do not internally use titles such as “senior,” but have levels to reflect seniority. Our Talent Acquisition team works closely with our employees to provide them the opportunity to grow their careers and demonstrate the scope of work in other ways aside from job titles. If you have further questions, please direct them to your recruiter and/or hiring manager, who can provide more insight.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

The base salary range for this full-time position in the location of San Francisco is:

$172,000$206,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI.  Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an affirmative action employer and inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. 

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Top Skills

Python
SQL
The Company
San Francisco, CA
523 Employees
On-site Workplace
Year Founded: 2016

What We Do

Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.

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