Weights & Biases
is hiring
Data Analyst
About Our Company
Weights & Biases: the AI developer platform.
Build better models faster, fine-tune LLMs, develop GenAI applications with confidence, all in one system of record developers are excited to use. W&B Models is the MLOps solution used by foundation model builders and enterprises who are training, fine-tuning, and deploying models into production. W&B Weave is the LLMOps solution for software developers who want a lightweight but powerful toolset to help them track and evaluate LLM applications.
Weights & Biases is trusted by over a 1,000 companies to productionize AI at scale including teams at OpenAI, Meta, NVIDIA, Cohere, Toyota, Square, Salesforce, and Microsoft.
Job Description &Â Responsibilities
You will collaborate with Data Scientists, Machine Learning Engineers, and Product Engineers to understand our business through data and analytics. Through this role you will have frequent opportunities to partner with decision-makers across the business to perform key analysis, build robust reporting, and un-block the business by answering questions via our data. Data Science at W&B is a pillar of the product, business, and culture; as such the Data Science team informs strategy directly, and partners with all parts of the business to build a data-first habit.
Responsibilities
- Collaborate across the business to create collective understanding of the business and product. create observability into our users and build collective understanding of our business and product.
- Pair with our Data Engineers to expand and improve our data models in our warehouse.
- Pair with our Data Scientists to apply and improve our statistical models for growth, churn, and other key business dynamics.
Requirements
Requirements
- Strong analytical and statistical intuition.
- History of writing succinct and impactful reports and analysis.
- History of writing easy-to-follow SQL and effective documentation for your projects.
- Experience in one of the following domains: SaaS startups, web applications, B2B Marketing, and/or the AI market.
- Basic knowledge of data orchestration / data pipeline tools (dbt, dagster, airflow, etc).
- Theoretical or practical understanding of machine learning workflows and terminology.
- Theoretical or practical understanding of web apps and best practices for logging and event instrumentation.
Core Skills
- Outgoing and friendly: You'll love this role if you enjoy connecting with real users day to day, helping them solve issues and understand good patterns for using our tools. Day to day you'll be answering questions and requests with a kind, thoughtful tone that makes users feel appreciated and connected to our team.
- Autonomous: If you work well in a self-directed environment, and proactively find ways to improve processes and collaborate with team members or engaged users, your initiative will really shine in this role.
- Curious and driven: Explore machine learning and learn more about the engineering stack and common ML workflows. Solve problems in both fast-paced, short term sprints and in larger, more long-term projects.
- Organized: A core part of engineering support at Weights & Biases is organizing feedback from many channels into a single, orderly stream. Your organization skills and time management will be key to running this process well.
What we offer
Benefits
- đïž Flexible time off
- đ©ș Medical, Dental, and Vision for employees and Family Coverage
- đ Remote first culture with in-office flexibility in San Francisco
- đ” Home office budget with a new high-powered laptop
- đ„ Truly competitive salary and equity
- đŒ 12 weeks of Parental leave (U.S. specific)
- đ 401(k) (U.S. specific)
- Supplemental benefits may be available depending on your location
- Explore benefits by country
The US base pay for this position ranges from $99,000 USD per year in our lowest geographic market up to $128,000 USD per year in our highest geographic market. Weights & Biases is committed to providing competitive salary, equity and benefits packages for all full-time employees. Individual compensation will be commensurate with the candidate's experience, qualifications, and geographic location.