Lead Data Scientist

About Us We are a growing Direct-to-Consumer (D2C) company leveraging data-driven strategies to create exceptional customer experiences and drive business growth. Our analytics and machine learning capabilities are fundamental to understanding customer behavior, optimizing operations, and delivering personalized experiences. We're seeking a skilled Lead/Senior Data Scientist to lead our machine learning initiatives and translate business challenges into actionable insights. Role Overview As a Senior Data Scientist, you will develop and implement machine learning models that directly impact key business metrics and customer experience. You'll work on high-impact projects including lead scoring, churn prediction, and customer segmentation while collaborating closely with data engineering and analytics teams. This role requires strong expertise in classical machine learning techniques, with an emphasis on building production-ready models that deliver measurable business value. Key Responsibilities ● Design, develop, and maintain machine learning models focused on lead scoring, churn prediction, customer segmentation, and other business-critical applications ● Build end-to-end ML pipelines, from data extraction and feature engineering to model deployment and monitoring ● Work with data engineering teams to ensure proper data infrastructure for ML workflows ● Collaborate with analytics teams to translate business problems into data science solutions ● Implement A/B testing methodologies to validate model effectiveness ● Monitor model performance in production and implement strategies for model maintenance and improvement ● Apply statistical analysis to extract meaningful patterns from large datasets ● Develop robust evaluation frameworks to measure model performance and business impact ● Create clear documentation for models, methodologies, and results ● Present findings and recommendations to technical and non-technical stakeholders ● Mentor junior data scientists and contribute to data science best practices ● Stay current with developments in machine learning and data science methodologies Qualifications Required ● Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field ● 5+ years of experience in data science or machine learning roles ● Strong proficiency in Python and its data science libraries (Pandas, NumPy, Scikit-learn, etc.) ● Expert knowledge of classical machine learning algorithms and techniques ● Experience building models for business applications such as lead scoring, churn prediction, and customer segmentation ● Hands-on experience with the full ML lifecycle, from data preparation to model deployment ● Experience with SQL and working with large datasets ● Understanding of statistical concepts and their practical applications ● Experience deploying models to production and implementing monitoring solutions ● Strong problem-solving skills and business acumen ● Excellent communication skills with the ability to explain complex concepts to diverse audiences Preferred ● Experience in D2C, e-commerce, or retail industries ● Familiarity with GenAI and Deep Learning technologies ● Knowledge of MLOps practices and tools ● Experience with cloud platforms (AWS, GCP, Azure) ● Familiarity with data visualization tools (Tableau, PowerBI, etc.) ● Experience with distributed computing frameworks (Spark) ● Understanding of experiment design and causal inference Technical Skills ● Programming Languages: Python (essential), R (beneficial) ● ML Libraries & Frameworks: Scikit-learn, XGBoost, LightGBM, Pandas, NumPy, SciPy ● MLOps Tools: MLflow, Kubeflow, or similar (beneficial) ● Databases & Query Languages: SQL, experience with data warehouses ● Cloud Platforms: Familiarity with AWS or GCP services ● Version Control: Git ● Data Visualization: Matplotlib, Seaborn, Plotly ● Collaboration Tools: Jupyter, modern data science workflows What We Offer ● Competitive salary and comprehensive benefits package ● Opportunity to work on impactful, business-critical projects ● Modern office in Mumbai with excellent facilities ● Collaborative, data-driven culture