Sr. Data Scientist

Microsoft Microsoft · Big Tech · Hyderabad, TS, IN · Data Science

Senior Data Scientist for Windows at Microsoft Hyderabad. Focuses on using advanced analytics, modeling, and data science to inform decision-making, optimize product performance, and maximize business impact for Windows products. Key responsibilities include improving search relevance, fine-tuning foundational models, driving growth through predictive insights, and leading initiatives in evaluation, corpus creation, metric design, and dataset development for diverse modalities. The role involves analyzing data, designing experiments, and deriving insights to influence product development and business strategy.

What you'd actually do

  1. As an expert in data science, you will take on the most complex business problems and guide the rest of the team in their efforts, helping them formulate approaches to solve challenging problems and discover new opportunities using well-defined algorithms and data sources in the context of customer, engineering, and business needs. You will build everything required to uncover business opportunities and generate actionable insights that move the needle.
  2. You will establish causality and conduct experiments to gain insights into quality, health of products, and customer usage. Additionally, you will lead initiatives in search relevance and evaluation, including corpus creation, metric design, and dataset development for diverse modalities, while fine-tuning foundational models to improve intelligent search experiences.
  3. You will engage with peers to produce clear, compelling, and data-backed hypotheses and insights which are actionable and influence product and service improvements—crafting the experience millions of customers have with Windows. You will also engage in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to increase the impact and applicability of your results. Through your analysis and research, you will curate and maintain Key Performance Indicators which show trends towards achieving a business goal.
  4. You will learn and excel in ways to find patterns in the data that are harder to detect but can lead to achieving our business objectives. Your analysis will not only show us what we’re doing right or wrong in our current methodology, but also what customer segments and strategies we should invest more in, and how, for achieving and exceeding our goals.

Skills

Required

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience
  • Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
  • Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
  • equivalent experience
  • managing structured and unstructured data
  • applying statistical techniques
  • reporting results

Nice to have

  • Bachelor’s Degree or higher in data science, Statistics, Computer Science, Engineering or another quant-focused field
  • 8+ years of experience with Data Science / Analytics
  • Experience with EDA
  • Inference analysis
  • Predictive analysis (Regression, Classification etc.,)
  • forecasting
  • Big Data technologies like Spark, Hadoop or other open- source technologies or SCOPE/COSMOS or U-SQL/ADL
  • Experience in one or more programming languages, preferably C#, Python or Java
  • A desire to mentor others
  • stay current with advances in the industry

What the JD emphasized

  • complex business problems
  • challenging problems
  • search relevance and evaluation
  • fine-tuning foundational models
  • diverse modalities
  • key business questions
  • deeply analyze the data
  • moves our business metrics
  • evaluate the return of investments
  • assess if investments are meeting customer and business promises
  • design and assess experiments
  • measure growth
  • derive insights
  • next wave of opportunities and problems to be solved
  • establish causality
  • conduct experiments
  • quality, health of products, and customer usage
  • intelligent search experiences
  • clear, compelling, and data-backed hypotheses and insights
  • actionable and influence product and service improvements
  • Key Performance Indicators
  • business goal
  • patterns in the data that are harder to detect
  • achieving our business objectives
  • customer segments and strategies we should invest more in

Other signals

  • driving future products via key data insights
  • transform data into actionable intelligence
  • improving search relevance
  • fine-tuning foundational models
  • driving growth through predictive insights
  • solving high-impact business problems for Windows through the power of data
  • build and deliver business Intelligence through data for experiences running on the next generation of Windows devices
  • Lead initiatives in search relevance and evaluation
  • dataset development for diverse modalities
  • Enhance foundational models through fine-tuning
  • deliver insights that power enterprise growth
  • understand the key business questions for customer-facing scenarios
  • set up the key performance indicators
  • deeply analyze the data to identify insights and experiment ideas that moves our business metrics
  • evaluate the return of investments on new ideas
  • assess if investments are meeting customer and business promises
  • design and assess experiments
  • measure growth
  • derive insights that help identify next wave of opportunities and problems to be solved
  • formulate approaches to solve challenging problems and discover new opportunities using well-defined algorithms and data sources
  • build everything required to uncover business opportunities and generate actionable insights that move the needle
  • establish causality and conduct experiments to gain insights into quality, health of products, and customer usage
  • lead initiatives in search relevance and evaluation
  • corpus creation
  • metric design
  • dataset development for diverse modalities
  • fine-tuning foundational models to improve intelligent search experiences
  • produce clear, compelling, and data-backed hypotheses and insights which are actionable and influence product and service improvements
  • crafting the experience millions of customers have with Windows
  • curate and maintain Key Performance Indicators which show trends towards achieving a business goal
  • find patterns in the data that are harder to detect but can lead to achieving our business objectives
  • show us what we’re doing right or wrong in our current methodology
  • what customer segments and strategies we should invest more in, and how, for achieving and exceeding our goals