Key Responsibilities :

- Collaborate with the Analytics Lead, Data Council, and IT teams to develop data-driven solutions.

- Translate data into actionable insights, communicate them to business stakeholders in an easy language.

- Design, build, and maintain scalable ELT pipelines for ingesting, transforming and processing data at scale.

- Experiment with ML algorithms (regression, classification, clustering, LLMs etc) to solve business problems.

- Transition ML models from prototypes to production, ensuring scalability, reliability and robustness.

- Deploy and manage AI/ML models on cloud-based platforms like AWS, Azure or Salesforce.

- Implement MLOps best practices including CI/CD pipelines, version control, model monitoring and retraining to maintain accuracy and performance.

- Integrate ML outputs into platforms like Bellevie app, Salesforce Screens and reporting dashboards.

Qualifications & Skills :

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

- 3 - 4 years of hands-on experience in data science, machine learning and production deployment of models

- Proficiency in Python and relevant libraries (eg. Pandas, Scikit-learn, XGBoost) along with strong SQL skills

- Strong understanding of predictive modeling techniques (supervised/unsupervised, clustering, NLP )

- Proven experience deploying AI/ML solutions on cloud platforms (AWS, Azure, Salesforce) with knowledge of MLOps practices like monitoring, version control and CI/CD

- Working knowledge of BI tools (Tableau, Power BI) for integrating ML insights into dashboards