Data Scientist

We’re looking for a senior data scientist to be the analytical backbone of the team - defining the metrics that matter, running experiments, and turning data into the decisions that shape the product. 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., 1. Define the metrics and measurement framework for a new product

1. build the dashboards and data foundations the team relies on.
2. Design and analyze experiments (A/B tests)
3. make clear, actionable recommendations.
4. Dig into user behavior to find opportunities and explain what’s driving the numbers.
5. Partner with product, engineering, and design to turn questions into analyses and analyses into decisions.
6. Raise the bar on analytical rigor and data quality across the team.

1. Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
2. 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)
3. 8+ years of experience in data science / product analytics
4. Strong SQL and a scripting language (e.g., Python)
5. solid grounding in statistics and experimentation
6. Track record of influencing product decisions with data
7. Ability to work independently and frame ambiguous problems, 15. 10+ years of experience communicating the results of analyses to leadership teams to influence the strategy
8. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
9. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
10. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
11. Experience as an early data scientist on a new product (0*1), including standing up metrics from scratch
12. Experience with consumer/social/community products, growth, or recommendation metrics