Job Responsibilities:

• Architect, build, and maintain data pipelines that will provision high quality data ready for analysis. This includes ingestion, exploration, modelling, and curation of high value data.
• Use innovative and modern tools, techniques, and architectures to automate the most-common, repeatable, and tedious data preparation and integration tasks partially or completely in order to minimize manual and error-prone processes and improve productivity with following processes:
• The data scientist should be curious and knowledgeable about new data initiatives and how to address them. This includes applying their data and/or domain understanding in addressing new data requirements. Establishing efficient design and programming patterns for scientists as well as for non-technical partners.
• Participate in ensuring compliance and governance during data use
• Build data expertise, act like a data owner for the company and manage complex data systems for a product or a group of products. He / She will be performing all of the necessary data transformations to serve products that empower data-driven decision making. He / She needs to understand the analytical objectives to make logical recommendations and drive informed actions
• Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy. He / She will be engaging with internal platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms. The data scientist contributes to innovations that fuel UPL’s vision and mission.

REQUIRED EDUCATION AND EXPERIENCE:

• Education and Experience

A bachelor’s or master’s degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field is required.

• Technical Knowledge/Skills

• At least 2-3 years of experience with advanced analytics tools for Object-oriented/object function scripting using languages such as Python, Scala, or similar.
• Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas, NLP, deep learning framework such as TensorFlow or Keras etc.
• Strong ability to design, build and manage data pipelines in PySpark and related technologies for data structures encompassing data transformation, data models, schemas, metadata, and workload management.
• The ability to work with both digital and business in integrating analytics and data science output into business processes and workflows.
• Exposure in machine Learning on both supervised and unsupervised models, experience on AWS ML platforms and able to build, train, deploy using Amazon Sagemaker.
• Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.).
• 2 + years’ experience with popular database programming in relational and nonrelational environments including on AWS Redshift, AWS Aurora, SQL Server, and similar platforms.

Location: Mumbai, India