As a Senior Data Scientist, you will apply your expertise in statistics, machine learning, and data analysis to extract valuable insights from structured and unstructured data. You will work closely with cross-functional teams to develop predictive models, improve business processes, and contribute to data-driven decision-making across the organization.
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 up-to-date 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.