Develop and deploy end-to-end data science and machine learning solutions for banking use cases, including cross-sell, up-sell, attrition, and hyper-personalization. Consult with stakeholders, identify opportunities in structured and unstructured data, improve ML delivery processes, and communicate technical findings clearly. The role requires production ML experience, generative AI application, predictive modeling, and strong Python, PySpark, and SQL skills.
Business Function
Group Technology and Operations (T&O) enables and empowers the bank with an efficient, nimble, and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability, and innovation. In Group T&O, we manage most of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels.
Roles & Responsibilities
- Driving Innovation: We are looking for Data Scientists across different levels to drive our journey towards becoming the most intelligent bank in the world.
- Stakeholder Consultation: Consult with business stakeholders to understand complex business challenges and devise robust, data-driven solutions.
- End-to-End Delivery: Develop, deploy, and productionise data-driven solutions from initial problem definition to final implementation.
- Process Improvement: Continuously refine and enhance existing processes for developing and deploying machine learning solutions.
- Opportunity Identification: Identify new opportunities for the bank by analyzing vast amounts of both structured and unstructured data.
- Model Development: Build predictive models (cross-sell, up-sell, attrition) to optimize customer management and drive revenue.
- Hyper-personalization: Develop and deploy hyper-personalization solutions for the consumer bank.
- Accountability & Communication: Act as a proactive owner of assigned tasks, ensuring accountability from inception to completion. Communicate complex technical work to business stakeholders with clarity and without jargon, ensuring alignment and understanding.
Requirements
- Experience - 6 - 9.5 years.
- Technical Foundations: A solid understanding of statistics, mathematical modeling, and machine learning.
- Critical Thinking: Demonstrated ability to analyze complex problems, identify root causes, and propose innovative data-driven solutions.
- Gen AI Skills: Practical experience in applying Generative AI frameworks like langchain, langflow, google adk etc and prompt engineering skills to enhance data science workflows and business outcomes.
- ML Proficiency: Proven experience building Decision Trees, Random Forest, Gradient Boosting, or other ML methods for both classification and regression problems.
- Production Experience: End-to-end experience taking solutions from development into a production environment.
- Programming Skills: Ability to program in Python, PySpark, and SQL.
- Soft Skills:
- Proactive & Accountable: A self-starter who takes ownership and accountability for all assigned tasks.
- Communication: Exceptional written and verbal communication skills; ability to explain technical outcomes in business-friendly terms, avoiding unnecessary jargon.
- Problem-Solving: Strong problem-solving skills, ability to work under pressure, and a positive, resilient attitude.
- Learning Agility: A demonstrated ability to self-learn new skills and technologies.
- Experience (Good to have): Experience in analytics and modeling within the banking domain is preferred but not mandatory.
Location:
Hyderabad - DTI Skyview SEZJob:
AnalyticsSchedule:
RegularEmployee Status:
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