About Exponentia.ai :

Exponentia.ai is a fast-growing AI-first technology services company, partnering with enterprises to shape and accelerate their journey to AI maturity. With a presence across the US, UK, UAE, India, and Singapore, we bring together deep domain knowledge, cloud-scale engineering, and cutting-edge artificial intelligence to help our clients transform into agile, insight-driven organizations.

We are proud partners with global technology leaders such as Databricks, Microsoft, AWS, and Qlik, and have been consistently recognized for innovation, delivery excellence, and trusted advisories.

About the Role :

We are seeking a highly skilled Senior Data Scientist to lead the design, development, validation, and deployment of customer propensity models on AWS. The ideal candidate will possess strong expertise in predictive modeling, advanced analytics, statistical methodologies, and machine learning, with a proven ability to translate business objectives into actionable insights and measurable outcomes.

This is a hands-on analytical leadership role that requires ownership across the complete model lifecycle, from problem framing and experimentation to deployment, monitoring, governance, and stakeholder engagement.

Key Responsibilities :

1. Propensity Modeling & Advanced Analytics :

- Lead stakeholder discussions to define target populations, prediction horizons, business outcomes, intervention strategies, and success metrics.

- Design and implement propensity modeling frameworks to support customer acquisition, retention, cross-sell, upsell, and engagement initiatives.

- Develop advanced machine learning models using statistical and predictive techniques.

- Drive feature engineering, model selection, tuning, validation, and performance optimization activities.

- Establish model acceptance criteria, evaluation methodologies, and analytical standards.

2. Model Development & Validation :

- Build predictive, segmentation, ensemble, and optimization models using structured and transactional datasets.

- Ensure robust handling of class imbalance, data leakage, bias mitigation, calibration, explainability, and model stability.

- Conduct hypothesis testing, statistical inference, experimentation, and performance benchmarking.

- Implement champion-challenger strategies and continuous model improvement frameworks.

3. AWS Machine Learning Platform Delivery :

- Develop and operationalize machine learning solutions using AWS services such as Amazon SageMaker, S3, Athena, and AWS Glue.

- Collaborate with Data Engineering teams to design scalable data preparation and feature engineering pipelines.

- Support deployment, monitoring, retraining strategies, and model lifecycle management.

- Ensure secure, scalable, and cost-effective utilization of AWS services.

4. Stakeholder Management & Business Impact :

- Translate analytical outputs into business recommendations, customer segments, prioritization frameworks, and intervention strategies.

- Present findings, insights, risks, and recommendations to technical and business stakeholders.

- Partner with business teams to measure model effectiveness and track business outcomes.

5. Mentorship & Governance :

- Mentor junior Data Scientists and provide guidance on analytical methodologies and best practices.

- Review code, experiments, documentation, and model performance reports.

- Define and enforce model governance, validation standards, monitoring frameworks, and documentation practices.

Ideal Candidate Profile :

- 5 - 7 years of experience in Data Science, Predictive Analytics, Customer Analytics, or Machine Learning.

- Strong expertise in propensity modeling, predictive analytics, segmentation, and statistical modeling.

- Hands-on experience building and deploying ML solutions on AWS.

- Strong understanding of model explainability, validation techniques, and model governance.

- Ability to convert complex business challenges into practical analytical solutions.

- Excellent communication and stakeholder management skills.

Preferred Qualifications :

- Master's degree preferred in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a related quantitative discipline.

- Bachelor's degree with strong relevant industry experience will also be considered.

Why Join Exponentia.ai? :

- Innovate with Purpose : Opportunity to create pioneering AI solutions in partnership with leading cloud and data platforms

- Shape the Practice : Build a marquee capability from the ground up with full ownership

- Work with the Best : Collaborate with top-tier talent and learn from industry leaders in AI

- Global Exposure : Be part of a high-growth firm operating across US, UK, UAE, India, and Singapore

- Continuous Growth : Access to certifications, tech events, and partner-led innovation labs

- Inclusive Culture : A supportive and diverse workplace that values learning, initiative, and ownership