Senior Data Scientist

As Sr Data Scientist, you will be responsible for a wide range of engagements listed below: - Formulates complex problems into hypotheses and proofs of concept for testing. Socializes this with the rest of the team and guides them to deliver on it. - Applies business acumen in analyses to extract meaningful and actionable information. - Communicates complex ideas and insights effectively to stakeholders with various levels of technical experience. - Leverages various analytical techniques, appropriate to solving the business problem at hand. - Performs research for solutions and solves problems efficiently to overcome data analytics challenges. - Engages in the collection, integration, analysis, and presentation of data for various business contexts - Understands good software development practices (versioning, peer reviews, refactoring, and pair programming), adapts them to the needs of the team and sets an example for others by following them. - Creates and maintains technical documentation of the scientific experimentations performed, preferably in the CRISP-DM framework or like. - Keeps up with the latest trends, technologies, and best practices in the field of Data Science and Engineering. Shares this knowledge with the rest of the data science team. - Does peer reviews of codes and approaches of fellow members of the data science team. - Provides mentorship to junior data scientists in the team. - Looks for improvements in data science delivery processes, actively seeks buy-in on the improvements from peers and managers, implements them in the team and monitors their adoption. Required Skills (Must have) Tech - Advanced programming knowledge in Python and SQL. - Advanced knowledge in Probability and Statistics, including hypothesis testing. - Advanced knowledge in Practical Machine Learning and awareness of the key-pitfalls in the practice of machine learning and approaches to addressing them. - Advanced knowledge of data visualization technologies like Tableau, and PowerBI, and comfortable using relevant libraries in Python like seaborn and matplotlib. - Experienced in modern development tools and writing code collaboratively. - Intermediate knowledge of Cloud technologies and experience in developing data science solutions in one or more cloud platforms. - Experienced in modern development tools, writing code collaboratively and developing solutions on cloud platforms. Non Tech : - Ability to recognize and pursue pragmatic alternatives vis-à-vis a perfect solution, balancing priorities of time with potential business impact. - Plan projects, break them down across individual data scientists in the team, track their performance and manage risks. - Ability to storyboard an entire presentation to a non-technical audience. - Ability to work independently to develop data science solutions, while also being able to work as part of a team to communicate findings and collaborate on solutions. - Strong written skills. This is required for submitting technical papers, whitepapers, and developing project documentations. - Technical leadership and mentorship to the community of data scientists in the organization. Required Skills (Good to have) Tech - Advanced knowledge in one or more areas besides Machine Learning – Operations Research, Natural Language Processing, Deep learning and its applications, Time Series forecasting at scale, Reinforcement Learning, Graph Machine Learning, Explainable Machine learning. - Advanced understanding of Cloud technologies and experience of deploying applications on cloud. Non Tech - Ability to solution critical business problems into its component parts and match each such part with an appropriate technical approach.