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Senior Data Scientist

Senior Data Scientist

  • Location India - Maharashtra - Pune
  • Travel required Yes - up to 10%
  • Job category IT&S Group
  • Relocation available Yes - Domestic (In country) only
  • Job type Professionals
  • Job code 134492BR
  • Experience level Intermediate
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Job summary

Senior Data Scientist will be part of a cross-disciplinary team, working closely with other data scientists, software engineers, data engineers, data managers, product owners and Portfolio managers.

Key Accountabilities:

  • Build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers.
  • Carry out data analyses to yield actionable business insights.
  • Act as the accountable person for the statistical methods used to enquire data sets, design of Machine Learning models & defining the end-to-end data lifecycle of a data science project from ideation to production
  • Translate problem statement to data architecture
  • Break down data architecture requirements to tasks for other team members
  • Appraise current design patterns (ex: AWS ) against requirements and adapt to the technology
  • Seek / promote automated pipelines / jobs
  • Communicate complex ideas in a digestible way to the business
  • Adhere to and advocate for data science best practices (e.g. technical design, technical design review, unit testing, monitoring & alerting, checking in code, code review, documentation).
  • Present results to peers and senior management.
  • Coach, mentor and support the data science squad on the full range of end-to-end data science and solutions development activities
Desired Criteria:
  • Bachelor or master’s degree in computer science, Engineering, Informatics, Information Systems or in another quantitative fields
  • Specialization in Machine Learning or Data Science will be an advantage
  • 8 to 12 years with minimum of 5 to 7 years relevant experience
  • Deep applied knowledge of data science tools and approaches across all data lifecycle stages.
  • Detailed understanding of underlying mathematical foundations of statistics and machine learning.
  • Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++)
  • Sophisticated SQL knowledge.
  • Experience with big data technologies (e.g. Hadoop, Hive, and Spark).
  • Knowledge of experimental design and analysis.
  • Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.
  • Strong stakeholder management and ability to influence.
  • Continuous learning and improvement mindset.

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