Head of Data Science

Key Responsibilities

•Lead and inspire a cross-functional Data Science Squad, ensuring high-quality delivery of end-to-end solutions across product, marketing, and operations domains.

•Set the long-term strategic vision for the Data Science squad, aligning with broader business goals of Organization's Functions and Brands that the team works with

•Display entrepreneurial traits by partnering with stakeholders to identify new AI/ML opportunities across the businesses, build the project pipeline, define business problems, and design data science solutions aligned to brand.

•Manage full model lifecycle—from data exploration and feature engineering to model training, validation, deployment, and performance monitoring.

•Role-model cross-functional leadership, partnering closely with Product, Tech, and Business counterparts

•Represent the Data Science squad in executive forums, contributing to center-wide governance, prioritization, and stakeholder engagement.

•Establish a culture of storytelling, impact, and continuous improvement across the team

•Mentor and grow team members while fostering a culture of experimentation and innovation.

Key Requirements :

•10+ years of experience in the data space, including hands-on exposure to data science, model development, and stakeholder delivery.

•Demonstrated experience working on B2C-focused models such as customer segmentation, recommender systems, marketing attribution, churn prediction, or personalization.

•Deep understanding of ML techniques, their practical applications, and limitations. Strong experience with modern data science languages and tools, including:

Languages: Python (preferred), SQL

Libraries/Frameworks: scikit-learn, XGBoost, LightGBM, pandas, NumPy, PySpark

Statistical foundation: Weights & Biases, A/B testing frameworks

Platforms: Databricks, AWS (S3, SageMaker), GCP (BigQuery, Vertex AI)

Visualization: Tableau, PowerBI

•Understanding of data engineering principles and experience working with large-scale structured and unstructured data is preferred.

•Proven ability to engage and influence stakeholders through effective storytelling and excellent communication skills. Experience in driving alignment and delivering impact in matrixed or global organizations.

•Exposure to product-led or consumer technology companies is strongly preferred.

•Deep understanding of ML Techniques, their practical applications, and limitations