Head of Data Science

Job description:

NPCI Data Analytics team is seeking a talented and motivated Data Scientist to join our team. As a Data Scientist, you will play a crucial role in modelling complex problems, uncovering insights, and identifying new opportunities using statistical, algorithmic, mining, and visualization techniques. You will be focused on utilizing NPCI product data and analytics to solve business problems by applying machine learning and deep learning techniques, conducting statistical analysis, and building high-quality predictive systems that are integrated with our services.

Education and experience:

BE/ B. tech with minimum of 15 years plus of experience in computer science with minimum 10 years in Data science - Machine learning, Data mining & engineering, Batch and Real time engineering, Deep learning, Artificial intelligence, Pattern recognition, ML Ops, Big Data management, Prescriptive analytics.

Job Responsibilities:

• Proficiency in data analysis to analyze the large data sets using tools like Python, Numpy, Pandas, Hive, Sci py, Tensorflow, Pytorch.
• Deep expertise in building real-time and batch analytics ETL solutions using big data technologies (Spark/ Kafka/KSql/Yarn/Hive/HDFS/Flink/Streaming etc) and NoSQL Stores
• Experience in deploying machine learning models at very large scale (>5000 tps)
• Developed applications on payment domain using business analytics and machine learning on specific areas as given below: -
• Anomaly detection (Fraud Risk Management) using supervised and unsupervised techniques with very large datasets
• Statistical, machine learning and graph-based models on Anti money laundering
• Recommending strategies to improve metrics like renewal rates, product adaptation rates, cross-sell/upsell rate, customer satisfaction, Customer grievances / disputes, business and technical decline etc.
• Define segmentation of customer base and recommend strategies for each segment.
• Delivery key predictive and descriptive models such as customer lifetime value models, and tenure, spend, and price models etc.

Management & Leadership capabilities:

• Interacting with business stake holders and proposing/implementing solutions to solve business problems.
• Working with like-minded team of Data Engineers and Data Scientists with expertise on working at large scale.
• Building scalable data processing platform and frameworks for serving Analytics and Data Science use cases.
• Building and managing a high performing team and supporting them through executing company's objectives.
• Critical thinking, design thinking and decision-making skills.
• Enabling data driven decision making skills to facilitate informed decisions that drive business growth.