Data Scientist (Core ML & Statistics)
Data Scientist (Core ML & Statistics)
Posted on :
24-08-2025
Employer Active
1 Vacancy
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Job Description
Who we are:
About the Role:
Were hiring a Data Scientist with strong foundations in statistics causal inference and experimental design. Your work will be centered on rigorous analysis: designing robust experiments validating assumptions and extracting clear insights from complex data. This is not a dashboards and KPIs role its about applying statistical thinking and careful modeling to answer hard questions and guide product direction.
We want someone who can think critically with data separate signal from noise and provide results that stand up to scrutiny.
What Youll Do:
- Design run and analyze A/B tests and other experimental frameworks.
- Apply statistical inference hypothesis testing and causal analysis to evaluate product changes.
- Build tune and interpret classical ML models (regression classification ranking) with a focus on explainability and robustness.
- Use rigorous exploratory analysis to uncover hidden patterns or validate product hypotheses.
- Develop reproducible workflows for experimentation and modeling.
- Collaborate with product and engineering to ensure experiments and analyses translate into well-grounded decisions.
- Contribute to a culture of statistical rigor clarity and curiosity.
What We Value:
- Deep understanding of statistics probability and causal inference.
- Comfort moving between theory and practice: from modeling assumptions to implementation details.
- Clear precise communication of methods assumptions and results.
- Patience to validate before scaling and rigor in separating correlation from causation.
Bonus Points:
- Experience with uplift modeling.
- Experience in product analytics or growth-focused DS.
- Experience working with Airflow BigQuery dbt or similar data infra.
- Experience in training and shipping models to production.
- Familiarity with basic experimentation pitfalls (SRM novelty effects power issues).
How We Hire:
- Online assessment: technical logic and fundamentals (Math/Calculus Statistics Probability Machine Learning/Deep Learning Code).
- Technical interview: deep dive into theory and reasoning for fraud detection (no code).
- Cultural interview.
If you are not willing to take an online quiz do not apply.
Employment Type
Full-Time
Key Skills
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