Über
The Role
The open AI evaluation platform redefining how the world's leading AI labs measure model performance is seeking a
Data Scientist
with expertise in
experimentation, causal inference, and retention analytics
to drive data-informed decision-making and optimize user engagement. In this role, you will design and analyze experiments (A/B tests, quasi-experiments), develop measurement frameworks for key metrics (DAU, WAU, MAU, retention), and provide actionable insights to improve product growth and user retention. Proficiency in
PySpark
is highly desirable to handle large-scale datasets efficiently.
What You'll Own
Experimentation & Causal Inference Design, implement, and analyze
A/B tests, multi-armed bandits, and quasi-experimental methods
to measure the impact of product changes. Apply
causal inference techniques
(e.g., difference-in-differences, propensity score matching, synthetic control, regression discontinuity) to estimate treatment effects in non-randomized settings. Collaborate with product, engineering, and marketing teams to define
hypotheses, success metrics, and statistical power requirements . Ensure
rigorous statistical validity
(e.g., controlling for biases, multiple testing corrections, confidence intervals).
Retention & Engagement Analytics Develop and refine
retention measurement frameworks
(e.g., cohort analysis, survival analysis, churn prediction). Define and track
core engagement metrics
(DAU, WAU, MAU, rolling retention, N-day retention) and diagnose trends. Identify
key drivers of retention
through segmentation, funnel analysis, and predictive modeling. Work with growth teams to
optimize onboarding, engagement loops, and monetization strategies .
Data Infrastructure & Scalable Analytics Build and maintain
scalable data pipelines
(using
PySpark, SQL, or big data tools ) to process and analyze large datasets. Develop
automated dashboards and reports
(e.g., Tableau, Looker, Metabase) to monitor experiment performance and retention trends. Ensure
data quality and consistency
in metric definitions across teams. Optimize queries and computations for
performance and cost efficiency
in distributed systems (e.g., Databricks, AWS EMR, GCP BigQuery).
Cross-Functional Collaboration Partner with
product managers, engineers, and marketers
to translate business questions into data-driven analyses. Present findings and recommendations to
executive stakeholders
in clear, actionable formats. Mentor junior data scientists and analysts on
best practices in experimentation and retention analytics .
What You'll Bring
3+ years
of experience in
data science, analytics, or experimentation
(or equivalent in academic research). Strong background in
statistics and causal inference
(hypothesis testing, Bayesian methods, experimental design). Hands-on experience with
SQL
and
Python
(Pandas, NumPy, SciPy, StatsModels, Scikit-learn). Proficiency in
experimentation tools
(e.g., Optimizely, Statsig, Eppo, or custom in-house systems). Experience defining and analyzing
retention metrics
(DAU/WAU/MAU, cohort retention, churn). Familiarity with
big data tools
(PySpark, Hadoop, or similar distributed computing frameworks). Highly Desirable: Expertise in PySpark
for large-scale data processing and analytics. Experience with
time-series forecasting, survival analysis, or uplift modeling . Knowledge of
ML for retention
(e.g., propensity models, clustering, recommendation systems). Experience with
data visualization tools
(Tableau, Looker, Plotly, Matplotlib/Seaborn). Background in
growth analytics, product analytics, or marketing analytics . Nice to Have: Advanced degree (MS/PhD) in
Statistics, Economics, Computer Science, or a quantitative field . Experience with
reinforcement learning or bandit algorithms
for dynamic experimentation. Knowledge of
MLOps or productionizing models
(e.g., MLflow, Airflow, Docker). Compensation Band
Their openings span more than one career level. The starting salary for this role is $200k and could range up to $400k USD, plus equity. The provided salary depends on many factors, such as work experience and transferable skills, business needs and impact, and market demands.
Benefits
Comprehensive health, dental, vision, and additional support programs. The opportunity to work on cutting-edge AI with a small, mission-driven team. A culture that values transparency, trust, and community impact. Visa sponsorship available.
About Our Client
This fast-growing startup is redefining what "better" means in AI. Built by researchers from UC Berkeley's SkyLab and backed by Felicis, Andreessen Horowitz, Kleiner Perkins, Lightspeed, and the University of California, this open evaluation platform has become the definitive source for understanding how AI models actually perform in the real world.
With over a million daily users and the trust of every major AI lab - including OpenAI, Google, and Anthropic - their crowdsourced benchmarks and human preference data power the decisions shaping the future of artificial intelligence. Their leaderboards aren't just influential; they're the industry standard.
Behind the platform is a team of researchers, engineers, and builders from UC Berkeley, Google, Stanford, DeepMind, and beyond - people who seek truth, move fast, and care deeply about craftsmanship and impact. They're building a company where deep expertise meets curiosity, and where the work genuinely matters.
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klicken Sie auf „Jetzt Bewerben“, um Ihre Bewerbung direkt auf deren Website einzureichen.