Bangalore, Karnataka, India
Information Technology
Full-Time
PivotRoots
Overview
Responsibilities
Advanced proficiency in:
- 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 clear, actionable formats
- Bachelor's or master’s degree in Statistics, Mathematics, Computer Science, or related quantitative field
- 2-4 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
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
- 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)
- 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
- Strong analytical and problem-solving abilities
- Good communication and presentation skills
- Business acumen
- Collaborative team player
- Strong organizational skills
- Ability to translate business problems into analytical solutions
- 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
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