Manager, Data Science
HybridHyderabad, Telangana, India
Job Summary
Lead and mentor a team of data scientists while owning end-to-end delivery of advanced data science solutions across pricing optimization, customer segmentation, and marketing analytics. Develop predictive models using Bayesian regression, machine learning techniques, and causal inference methods like A/B testing and Difference-in-Differences. Deploy operationalized models on AWS SageMaker and apply explainability frameworks such as SHAP to translate insights into actionable business recommendations. Collaborate with clients and stakeholders to define problems, validate approaches, and establish governance best practices for model development and reproducibility. Proactively identify opportunities where analytics drive measurable value in revenue, profitability, and market-share objectives.
Required Qualifications
- 9+ years of hands-on experience in Data Science, Advanced Analytics, or a related quantitative field
- experience leading or mentoring data scientists
- Strong programming skills in Python
- experience with pandas
- experience with NumPy
- experience with scikit-learn
- Strong SQL skills
- Strong understanding of applied statistics
- Strong understanding of probability
- Strong understanding of regression
- Strong understanding of hypothesis testing
- Strong understanding of model evaluation
- Strong understanding of statistical inference
- Hands-on experience with Bayesian Modelling & Optimization
- Hands-on experience with K-Means
- Hands-on experience with Gaussian Mixture Models (GMM)
- Hands-on experience with DBSCAN
- Hands-on experience with Regression Modelling
- Hands-on experience with Random Forest
- Hands-on experience with Decision Trees
- Hands-on experience with Support Vector Machines (SVM)
- Hands-on experience with Other supervised and unsupervised machine learning techniques
- Strong experience in feature engineering
- Strong experience in model selection
- Strong experience in validation
- Strong experience in tuning
- Strong experience in performance evaluation
- Hands-on experience with SHAP or other model explainability techniques
- Experience with pricing optimization
- Experience with price elasticity
- Experience with revenue optimization
- Experience with related decision science problems
- Hands-on experience with AWS
- Hands-on experience with AWS SageMaker
- Experience in financial services, retail, media, marketing, loyalty, payments, or customer analytics
Desired Qualifications
- experience with AWS SageMaker
- Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Engineering, or a related quantitative discipline
- Experience with Marketing Mix Modelling (MMM)
- Experience with adstock
- Experience with saturation
- Experience with response curves
- Experience with media budget optimization
- Experience with A/B testing
- Experience with experimental design
- Experience with causal inference
- Experience with geo experiments
- Experience with Difference-in-Differences
- Experience with Synthetic Control
- Experience with Regression Discontinuity
- Ability to evaluate causal relationships
- Ability to quantify uncertainty
- Ability to translate experimental results into business recommendations
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