Senior Data Scientist

Microsoft Microsoft · Big Tech · Vancouver, BC +3 · Data Science

Senior Data Scientist role within Microsoft's Customer Experience and Success (CE&S) Business Intelligence team, focusing on developing data-driven solutions and ML models, including those using foundation models and LLMs, to optimize customer experience and support operations. The role involves collaborating with engineering, product, and business teams to deploy solutions and enhance data science practices.

What you'd actually do

  1. Be a self-starter with a demonstrated track record of providing technology vision and driving them through.
  2. Collaborate with partner teams (engineers and analysts) to deliver end-to-end systems and experiences.
  3. Develop Machine Learning models and solutions using classical algorithms as well as foundation models.
  4. Utilize LLMs and other AI technologies to revolutionize data science practices within the team, enhancing the speed, accuracy, and scalability of data analysis and insight generation.
  5. Apply your knowledge in quantitative analysis, data mining, and the presentation of data to inform decision-making.

Skills

Required

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience OR equivalent experience.
  • 5+ years experience building machine learning models and writing production level code in Python.

Nice to have

  • Fluent in tools for navigating and analyzing data (SQL, Python, Databricks, Synapse, AzureML, Fabric, etc.); experience with Azure Cloud.
  • Excellent quantitative, data modeling, and statistical skills. Examples include causal inference, resampling techniques, mixed effects models, significance tests, etc, with machine learning algorithms for forecasting, clustering, classification, recommendation systems, NLP, etc.
  • Excellent written and oral communication skills, particularly the ability to synthesize complex problems/scenarios into easy-to-understand concepts.
  • Creative, innovative, and organized thinker with high attention to detail and self-driven to continuously learn and bring a growth mindset to problem-solving with effective time management in complex, ambiguous, deadline-driven environments.
  • 5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.

What the JD emphasized

  • 5+ years experience building machine learning models and writing production level code in Python.

Other signals

  • Develop Machine Learning models and solutions using classical algorithms as well as foundation models.
  • Utilize LLMs and other AI technologies to revolutionize data science practices within the team, enhancing the speed, accuracy, and scalability of data analysis and insight generation.