Manager - AI​/ML

Key Responsibilities

- Engage with clients to understand their business objectives and challenges, providing data-driven recommendations and AI/ML solutions that enhance decision-making and deliver tangible value.
- Translate business needs - particularly within financial services domains such as marketing, risk, compliance and customer lifecycle management into well-defined machine learning problem statements and solution workflows.
- Solve business problems using analytics and machine learning techniques:
Conduct exploratory data analysis, feature engineering, and model development to uncover insights and predict outcomes.
- Develop and deploy ML models, including supervised and unsupervised learning algorithms and model performance optimization.
- Design and implement scalable, cloud-native ML pipelines and APIs using tools like Python, Scikit-learn, Tensor Flow, and PyTorch.
- Collaborate with cross-functional teams to deliver robust and reliable solutions in cloud environments such as AWS, Azure, or GCP.
- Be a master storyteller for our services and solutions to our clients at various stages of engagement such as pre-sales, sales, and delivery using data-driven insights.
- Stay current with developments in AI, ML modelling, and data engineering best practices, and integrate them into project work.
- Mentor junior team members, provide guidance on modelling practices, and contribute to an environment of continuous learning and improvement.

Job Requirements

- 4 to 7 years of relevant experience in building ML solutions, with a strong foundation in machine learning modelling and deployment.
- Strong exposure to banking, payments, fintech or Wealth/Asset management domains, with experience working on problems related to:
- Marketing analytics for product cross-sell/up-sell and campaign optimization
- Customer churn and retention analysis
- Credit risk assessment and scoring models
- Fraud detection and transaction risk modeling
- Customer segmentation for personalized targeting
- Experience in developing traditional ML models across business functions such as risk, marketing, customer segmentation, and forecasting.
- Bachelor’s or Master’s degree from a Tier 1 technical institute or MBA from Tier 1 institute
- Proficiency in Python and experience with AI/ML libraries such as Scikit-learn, Tensor Flow, PyTorch.
- Experience in end-to-end model development lifecycle: data preparation, feature engineering, model selection, validation, deployment, and monitoring.
- Eagerness to learn and familiarity with developments in Agentic AI space
- Strong problem-solving capabilities and the ability to independently lead tasks or contribute within a team setting
- Effective communication and presentation skills for internal and client-facing interactions
- Ability to bridge technical solutions with business impact and drive value through data science initiatives