Senior Data Scientists We are seeking experienced data scientists to evaluate real-world data science work for an advanced AI research project. You will define what high-quality data science looks like, create clear scoring criteria, and evaluate completed analyses with detailed written reasoning. What You’ll Do Develop grading criteria for data analyses, predictive models, dashboards, experiments, metric frameworks, and business recommendations

Evaluate AI-generated and human-created data science work

Review SQL queries, Python analyses, statistical methods, visualizations, assumptions, and conclusions

Score work for technical accuracy, analytical rigor, business relevance, clarity, and actionability

Assess experiment designs, A/B tests, causal claims, metric definitions, and executive recommendations

Provide detailed, evidence-based written justifications for every score

Apply consistent evaluation standards across different tasks

Incorporate reviewer feedback and improve your work quickly Who Can Apply Relevant backgrounds include: Data Scientists, Senior Data Scientists, Staff Data Scientists, Principal Data Scientists, Lead Data Scientists, Product Data Scientists, Growth Data Scientists, Business Data Scientists, Decision Scientists, Analytics Scientists, Applied Data Scientists, Experimentation Scientists, Causal Inference Scientists, Statistical Scientists, Quantitative Researchers, Research Scientists, Applied Scientists, and Machine Learning Scientists.

Leadership backgrounds may include: Data Science Managers, Heads of Data Science, Directors of Data Science, Analytics Directors,



Product Analytics Leads, Experimentation Leads, Insights Directors, Decision Science Managers, Quantitative Analytics Leads, and Data Strategy Consultants.

Relevant

Areas of Expertise Product, growth, marketing, operations, marketplace, or business data science

A/B testing, controlled experiments, holdout tests, and experimentation platforms

Experiment design, statistical power, sample sizing, and significance testing

Causal inference, quasi-experimental methods, and observational analysis

Metric definition, KPI development, north-star metrics, and guardrail metrics

Funnel analysis, conversion analysis, retention, engagement, and cohort analysis

Customer segmentation, churn modeling, forecasting, and predictive analytics

Regression, classification, clustering, time-series analysis, and statistical modeling

Dashboard development, data visualization, and executive reporting

Translating technical findings into clear business recommendations

Reviewing analytical work for errors, bias, leakage, weak assumptions, or unsupported conclusions Tools and Technologies Experience with one or more of the following is valuable: Python, SQL, R, pandas, NumPy, SciPy, scikit-learn, statsmodels,



Jupyter, Spark, Databricks, Snowflake, BigQuery, Redshift, Tableau, Power BI, Looker, Mode, Amplitude, Mixpanel, Excel, dbt, Git, Airflow, and contemporary experimentation platforms.

Requirements 5+ years of professional data science experience in an industry environment

Strong hands-on experience with SQL and Python or R

Deep understanding of statistics, experiment design, A/B testing, and analytical methodology

Experience defining metrics and evaluating business or product performance

Ability to assess whether an analysis, model, or recommendation is technically sound

Strong written communication and the ability to explain professional judgment clearly

Detail-oriented, consistent, and comfortable receiving structured reviewer feedback Preferred Background Experience in product, growth, business operations, marketplace, consumer, or technology data science

Experience presenting findings to executives, product leaders, or business stakeholders

Experience reviewing the work of other data scientists or analysts

Background at a technology company, consulting firm, research organization, or data-driven consumer business

Prior experience with AI evaluation, model training, data annotation, rubric development, benchmark creation, or human-feedback projects This opportunity is ideal for experienced data professionals who can distinguish rigorous, decision-ready data science from technically plausible but weak or misleading analysis. We are a referral partner of the client

📌 Senior Data Scientist | Remote (India)
🏢 The Ai Training
📍 India