[{"Salary":null , "Remote_Job":false , "Posting_Title":"Data Scientist" , "Is_Locked":false , "City":"Mumbai" , "Industry":"Retail" , "Job_Description":"
Who is this for If building sophisticated statistical models and conducting rigorous causal analysis to drive business impact excites you, this is your opportunity. Fornax is seeking a Data Scientist who combines advanced analytical techniques with business acumen to solve complex challenges in the Retail domain.
We are looking for a technically proficient data scientist who excels at causal inference, experimental design, and predictive modeling while translating complex methodologies into actionable business insights.
Key Responsibilities
Advanced Analytics Causal Inference (30%)
- Design and implement causal inference studies using difference-in-differences (DiD), regression discontinuity, synthetic control methods, and propensity score matching
- Conduct rigorous A/B testing and experimental design to measure treatment effects and validate business interventions
- Build predictive models using machine learning techniques (random forests, gradient boosting, neural networks) for customer behavior, demand forecasting, and churn prediction
- Perform time series analysis and forecasting for sales, inventory, and market trends
- Apply advanced statistical methods to identify and quantify causal relationships in observational data
- Develop attribution models to measure the incremental impact of marketing campaigns and business initiatives
Statistical Modeling Machine Learning (25%)
- Build and deploy supervised and unsupervised learning models for classification, regression, clustering, and recommendation systems
- Implement feature engineering pipelines and model selection frameworks to optimize predictive performance
- Develop customer segmentation models using clustering algorithms and behavioral analytics
- Create price optimization and dynamic pricing models using elasticity analysis
- Build survival analysis models for customer lifetime value and retention prediction
- Apply natural language processing (NLP) techniques for sentiment analysis and customer feedback analysis
Experimentation Testing (20%)
- Design and analyze randomized controlled trials (RCTs) and quasi-experimental studies
- Implement Bayesian A/B testing frameworks for sequential experimentation
- Develop power analysis and sample size calculations for experimental design
- Build multi-armed bandit algorithms for dynamic optimization
- Create test-and-learn frameworks for rapid business experimentation
- Monitor and diagnose experiment validity issues including selection bias, spillover effects, and non-compliance
Strategic Decision Support Communication (25%)
- Translate complex analytical findings into clear, actionable recommendations for business stakeholders
- Partner with business leaders to frame strategic questions as testable hypotheses and analytical problems
- Create data visualizations and executive summaries that communicate technical insights to non-technical audiences
- Develop and maintain strategic KPI frameworks aligned with business objectives
- Lead cross-functional analytics projects from problem formulation to implementation
- Provide data-driven recommendations for product launches, market expansion, and customer acquisition strategies
Requirements Technical Skills
- Causal Inference: Difference-in-differences (DiD), instrumental variables, regression discontinuity design (RDD), propensity score matching, synthetic control methods
- Machine Learning: Supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), ensemble methods, deep learning
- Statistical Analysis: Hypothesis testing, Bayesian inference, time series analysis, survival analysis, panel data methods
- Programming: Python (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow) and/or R (tidyverse, caret, causalimpact)
- Experimentation: A/B testing, experimental design, power analysis, multi-armed bandits
- Data Tools: SQL, Git, cloud platforms (AWS/GCP/Azure), visualization tools (Tableau, Power BI, or similar)
Education Experience
- 2+ years of experience in data science, applied research, or analytics consulting, preferably in retail or e-commerce
- Proven track record of applying causal inference methods to business problems
- Experience collaborating with cross-functional teams and communicating technical concepts to business stakeholders
","Work_Experience":"1-3 years","Job_Type":"Full time","Job_Opening_Name":"Data Scientist" , "State":"Maharashtra" , "Currency":"INR" , "Country":"India" , "Zip_Code":"400055" , "id":"73908000003570486" , "Publish":true , "Date_Opened":"2025-11-02" , "Keep_on_Career_Site":false}]
