What you will do:

• Work on Data science projects in close collaboration with the Data Engineering team, Product owners and business leaders to deliver high value business capabilities.

• Be responsible for high quality data science solutions with respect to accuracy and coverage.

• Be accountable for solutions scalability, stability, and business adoption.

• Responsible for maintaining proper documentation and further code-reusability principles

• Responsible for ownership of algorithms and its enhancements/optimizations as per business requirement

• Collaborate with Senior data scientists in long term vision, strategy, and solution roadmap to align with bigger business objectives and mission critical priorities of the organization.

• Responsible to pitch ideas, present solutions and influence senior leaders with strong business value propositions.

What you will need:

• 1-3 years hands-on experience building Machine Learning Models, Natural Language Applications or artificial intelligence business capabilities.

• Bachelor s Degree in a quantitative field (math, stat, computer science, engineering, etc.) required; Master s degree is preferred and PhD a strong plus.

• Experience and proficiency with Python coding, Big data technologies like PySpark and important python machine learning libraries and statistical packages.

• Working experience with SQL/relational databases (e.g., Oracle) and NoSQL databases (e.g., MongoDB, Neo4j), Linux and shell scripting.

• Hands on Experience of working in Deep Learning Models and related frameworks like TensorFlow, Keras, PyTorch etc.

• Experience working within cloud computing environment such as Azure or AWS.

• Demonstrated ability to translate quantitative analysis into actionable business strategies.

• Strong working knowledge of Lean product principles, Software development lifecycle, IT and data science/machine learning topics

• Practical, intuitive problem solver with a demonstrated ability to translate business objectives into actionable data science tasks and translate quantitative analysis into actionable business strategies

• Ability to work collaboratively with a variety of business, data science and technical stakeholders