Full Stack Data Scientist

We are looking for data scientists who are excited to work on Machine Learning/Deep Learning projects. The ideal candidate will have good Machine Learning/Deep learning knowledge, and hands on experience solving complex real-world ML/DL problems. We want people who are excited to solve the hard problems, eager to work with a larger team of data scientists & engineers and ready to make business impact in areas related to Pricing, Claims, Sales, Marketing, Operations or any other ongoing research into the organisation.

Duties and Responsibilities:

• Ability to code & implement reusable Machine learning frameworks.
• Work with data engineers to source, analyse & engineer features , perform data augmentation.
• Ability to design and build an efficient data pipeline that can train, test & deploy high Quality models into production to run at scale.

The role may involve independent tasks or supporting senior team members as per project requirements

Keep up to speed with the latest industry & technology SOTA developments in machine learning/ Deep learning

Qualification, Experience, Technical and Functional Skills

• B.Tech/B.E/MCA or Mtech in Computer science/electronics/electrical engineering/Statistics tier 1 colleges/ universities.
• 4+ years of hands-on experience with Python and SQL (R is a plus)
• 4+ years of data science/analytics experience
• Experience with traditional Machine Learning
• Experience with Deep Learning (especially Computer Vision and/or Natural Language Processing)
• Well-developed analytical, logical and problem solving skills
• Advanced ability to perform exploratory data analysis, visualize data and answer business questions with data and analytics
• Familiarity with data management tools
• Working knowledge of Statistics and familiarity with common data science toolkits
• Excellent communication (written and oral) & technical writing skills

Optional skills:

• Prior experience in P&C and L&H Insurance analytics (Claims, Pricing, Marketing)
• Professional software development experience including documentation and testing
• Working experience in containerized, cloud-based environments, especially Microsoft Azure
• Experience with developing and maintaining CI/CD pipelines
• Experience in designing, developing, deploying and operating scalable RESTful micro-services
• Knowledge and experience in DBMS technologies
• Knowledge and experience in Monitoring systems
• Knowledge on software architecture design principles
• Experience working in a cross-functional and distributed agile team
• Up to date knowledge on recent ML research topics and their applications

Key Competencies

Sound quantitative and logical aptitude.

Self-motivated and organized, eager to learn and expand his/her knowledge

Key technical skills: Mentioned above. Especially – Python, Machine learning & Deep Learning