Havas CSA is seeking a Data Scientist with 2-4 years of experience to contribute to advanced analytics and predictive modelling initiatives The ideal candidate will combine strong statistical knowledge with practical business understanding to help develop and implement models that drive customer value and business growth Responsibilities Implement and maintain customer analytics models including CLTV prediction propensity modelling and churn prediction Support the development of customer segmentation models using clustering techniques and behavioural analysis Assist in building and maintaining survival models to analyze customer lifecycle events Work with large-scale datasets using BigQuery and Snowflake Develop and validate machine learning models using Python and cloud-based ML platforms specifically BQ ML ModelGarden and Amazon Bedrock Help transform model insights into actionable business recommendations Collaborate with analytics and activation teams to implement model outputs Present analyses to stakeholders in transparent actionable formats Qualifications Bachelor s or master s degree in Statistics Mathematics Computer Science or related quantitative field 1-2 years experience in applied data science preferably in marketing retail Experience in developing and implementing machine learning models Strong understanding of statistical concepts and experimental design Ability to communicate technical concepts to non-technical audiences Familiarity with agile development methodologies Technical Skills Advanced proficiency in SQL and data warehouses BigQuery Snowflake Python for statistical modeling Machine learning frameworks scikit-learn TensorFlow Statistical analysis and hypothesis testing Data visualization tools Matplotlib Seaborn Version control systems Git Understanding of Google Cloud Function and Cloud Run Experience with Customer lifetime value modeling RFM analysis and customer segmentation Survival analysis and hazard modeling A B testing and causal inference Feature engineering and selection Model validation and monitoring Cloud computing platforms GCP AWS Azure Key Projects Deliverables Support development and maintenance of CLTV models Contribute to customer segmentation models incorporating behavioral and transactional data Implement survival models to predict customer churn Support the development of attribution models for marketing effectiveness Help develop recommendation engines for personalized customer experiences Assist in creating automated reporting and monitoring systems Soft Skills Strong analytical and problem-solving abilities Good communication and presentation skills Business acumen Cooperative team player Strong organizational skills Ability to translate business problems into analytical solutions Growth Opportunities Work on innovative data science projects for major brands Develop expertise in cutting-edge ML technologies Learn from experienced data science leaders Contribute to impactful analytical solutions Opportunity for career advancement We offer competitive compensation comprehensive benefits and the opportunity to work with leading brands while solving complex analytical challenges Join our team to grow your career while making a significant impact through data-driven decision making Contract Type Permanent Here at Havas across the group we pride ourselves on being committed to offering equal opportunities to all potential employees and have zero tolerance for discrimination We are an equal opportunity employer and welcome applicants irrespective of age sex race ethnicity disability and other factors that have no bearing on an individual s ability to perform their job Job Type Full-time Pay 1 000 000 00 - 1 300 000 00 per year Benefits Health insurance Life insurance Paid sick time Paid time off Provident Fund Work from home Ability to commute relocate Andheri Mumbai Maharashtra Reliably commute or planning to relocate before starting work Preferred Experience Data science 2 years Preferred Work Location In person

📌 Data Scientist (Maharashtra)
🏢 PivotRoots - A Havas
📍 Maharashtra