National Payments Corporation of India jobs - Lead Data scientist

1. Post: Lead Data scientist

2. Roles and Responsibilities

a. NPCI Data Analytics team is looking for a data scientist who will be primarily responsible for modeling complex problems, discovering insights, and identifying opportunities through the use of statistical, algorithmic, mining, and visualization techniques.

b. The primary focus will be to propose innovative ways to utilize NPCI products data and analytics to solve business problems by applying ML and DL techniques, doing statistical analysis, validating your findings using an experimental and iterative approach, and building high-quality prediction systems integrated with our services. Should have strong business understanding, analytical and problem-solving skills, and programming knowledge.

3. Job Responsibilities:

a. Interact with cross-functional teams to foster a data driven payments organization. Create data pipeline for models which includes data preparation, data cleaning, transformations

b. Work on big data systems such as Hadoop and Hive and spark for feature generation and data processing. Develop data streaming applications and REST services for model serving in production.

c. Compile complex predictive model packages for production deployment; support model installations, and monitor and calibrate production models. Perform analyses on various data sources and generate reports and deeper insights at the aggregate level, as well as at the model level. Interpret and present these results to a non-technical audience

d. Find opportunities to create and automate repeatable analyses or build self-service tools for business users

e. To build deep learning models on text image and voice domain which assist used in payments domain. Design experiments, test hypotheses, and build models utilizing the traditional datasets and graph data

4. Desired Candidate Profile

a. Bachelor’s Degree in computer science or Advanced degree with 5-8 years’ experience with 3+ years of work experience as a Data scientist

b. Good understanding of concepts in data science, data structures, and databases. Fluent in SQL and proficiency in programming either Python, Java, or scala

c. Proficient in machine learning (SVM, GLM, boosting, random forest) and deep neural networks. Visualization tools/programming; e.g. Tableau, D3

d. Familiarity with basic principles of distributed computing and distributed databases. A strong passion for data with the ability to drive analytics capability development using advanced data techniques and statistical methodologies

e. Strong communication skills and the ability to distill information and results into simple concepts and actionable insights for a variety of audiences. Experience in leading or participating complex quantitative data driven efforts to drive business development in support of operations

5. Perks and Benefits: As per Industry Standards