Senior Data Scientist

Microsoft Microsoft · Big Tech · Bengaluru, KA, IN · Data Science

Senior Data Scientist role within Microsoft's Industry Solutions Engineering team, focusing on developing AI and cloud-based solutions for customers. The role involves data acquisition, preparation, model development, evaluation, and deployment at scale, with a strong emphasis on customer-facing project delivery and innovation.

What you'd actually do

  1. You will acquire the data necessary for your project plan and develop usable data sets for modeling. You’ll also update internal best practices for data collection and preparation, and contribute to data integrity conversations with customers.
  2. You will evaluate your team’s models and recommend improvements as necessary, drive best practices for models, and develop operational models that run at scale. You’ll also conduct thorough reviews of data analysis and modeling techniques, and identify and invent new evaluation methods.
  3. You will research and maintain a deep knowledge of the industry, including trends and technologies, so that you can identify strategy opportunities and contribute to thought leadership best practices. You’ll also write extensible code that spans multiple features, and develop expertise in proper debugging techniques.
  4. You will define business, customer, and solution strategy goals, and partner with other teams to identify and explore new opportunities. You’ll also apply a customer-oriented focus to understand their needs, and help drive realistic customer expectations.

Skills

Required

  • Data Science
  • Mathematics
  • Statistics
  • Econometrics
  • Economics
  • Operations Research
  • Computer Science
  • data management
  • statistical techniques
  • reporting results
  • customer-facing project-delivery
  • professional services
  • consulting

Nice to have

  • AI
  • cloud-based solutions
  • modeling
  • data collection
  • data preparation
  • data integrity
  • model evaluation
  • best practices for models
  • operational models
  • data analysis
  • modeling techniques
  • evaluation methods
  • industry trends
  • technologies
  • strategy opportunities
  • thought leadership
  • extensible code
  • debugging techniques
  • business strategy
  • customer strategy
  • solution strategy
  • open source

What the JD emphasized

  • customer-facing
  • develop operational models that run at scale
  • identify and invent new evaluation methods

Other signals

  • customer-facing
  • AI and other cloud-based solutions
  • develop usable data sets for modeling
  • evaluate models and recommend improvements
  • develop operational models that run at scale
  • identify and invent new evaluation methods