Job Description
- Job Description:
- Lead statistical analysis and modeling efforts for program evaluation and business impact assessment
- Design and execute evaluation methodologies (e.g., A/B testing, quasi-experimental designs, causal inference)
- Apply advanced statistical techniques such as regression, hypothesis testing, time-series analysis, and multivariate analysis
- Develop predictive and explanatory models to assess program outcomes and performance
- Translate complex analytical findings into clear, actionable insights for business and leadership stakeholders
- Work closely with cross-functional teams (product, business, strategy) to define evaluation metrics and success criteria
- Ensure data quality, statistical validity, and reproducibility of analyses
- Mentor junior team members and review analytical work for rigor and accuracy
- Collaborate, coach, and learn with a growing team of experienced Data Scientists.
- Requirements:
- 6-7 years of experience in Data Science, Advanced Analytics, or Statistical Modeling roles
- Strong foundation in statistics and probability with hands-on application in real-world programs
- Proven experience in program evaluation, impact measurement, or policy/business evaluation
- Expertise in statistical modeling techniques (linear/logistic regression, mixed models, time-series, causal models)
- Proficiency in Python or R for statistical analysis and modeling
- Strong SQL skills for data extraction and analysis
- Experience working with large, complex datasets
- Excellent communication skills with the ability to explain statistical results to non-technical audiences
- Experience with causal inference frameworks (PSM, DiD, uplift modeling, Bayesian methods)
Benefits:
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.***Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.***
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