Senior Data Scientist
Responsibilities and Key Result Areas
- Work with internal Business/Product units and external customers, engineering and research teams in building predictive models in healthcare and lifestyle areas
- Manipulate and analyze complex, high-volume, high-dimensionality data from varying sources
- Setup, Analyze and interpret the results of product experiments. Answer questions by using appropriate statistical techniques on available data
- Communicate complex quantitative analysis in a clear, precise, and actionable manner
- Design, develop and implement solutions and implementations using R, Python and HSDP ML libraries
- Create/Leverage algorithms to extract Patterns from large data sets.
- Define and adhere to scalable, efficient processes for model development, model validation, model implementation and large scale data analysis.
- Develop metrics and prototypes that can be used to drive business decisions.
- Identify emergent trends and opportunities for future client growth and development
- Drive the collection of new data and the refinement of existing data sources
- Interface with stakeholders for Requirements understanding, architecture clarifications etc.
- Support in project estimation, planning and risk management activities. Identify and escalate risks in time
- Ensure compliance to the Quality Management System and regulatory requirements
Know-how & Skill Set
- A Ph.D. or Master’s Degree in applied statistics, computer science, Applied maths, data mining, machine learning or operations research.
- Strong background in Maths (Linear Algebra, Stats, Linear/Quadratic programing, Calculus)
- Deep understanding of predictive modeling concepts, machine-learning approaches like clustering, classification, recommendation, kernel tricks, optimization algorithms and NLP
- Extensive experience solving analytical problems using quantitative approaches (e.g. Bayesian Analysis, Dimensional Data Representations, and Multi-scale Feature Identification, Dimensionality reductions, Neural Nets).
- Strong Proficiency with statistical analysis languages (e.g. R, Python)
- Ability to develop hypothesis, test them with experiments, Statistical analysis and predictive modelling
- Have done projects on real data (Both Structured and Unstructured )
- Min of 4-5 years of experience in delivering data science outcomes, solving complex analytical problems using quantitative approaches blending analytical, mathematical and technical skills.
- Good hold on data visualization and presentation.
- Strong passion for empirical research and for answering hard questions with data
- Preferable – Healthcare domain, Experience with big data tools (e.g., Spark, H20)
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