Data Scientist II

Responsibilities

• Machine Learning Model Development: Design and implement machine learning algorithms to enhance product. This includes developing and evaluating models and preparing large-scale datasets for training and testing.
• Data Analysis & Insights: Analyze usage and interaction data to drive product decisions and improvements to experience.
• Experimentation & Optimization: Design and execute experiments (A/B tests) to evaluate the impact of new features or model changes. Monitor model performance and user engagement metrics and iterate on solutions to optimize outcomes. You will own the end-to-end workflow of data science projects, from hypothesis formulation to deploying validated improvements.
• Cross-Functional Collaboration: Work closely with a multi-disciplinary team of engineers, product managers, researchers, and UX designers in the organization.

Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• 3+ years of hands-on experience in data science or a closely related role, building and deploying machine learning models to solve real-world problems.
  
• Deep understanding of machine learning algorithms and statistical techniques. You should be skilled in applying a broad range of methods – including regression, classification, clustering, and recommendation algorithms. Experience in training models for predictive analytics and optimization is highly valued.
  
• Solid programming skills in Python (or equivalent) for data analysis and development. Familiarity with machine learning frameworks and libraries is expected.

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

• Experience with Azure Analytics stack, e.g., Azure Synapse, Kusto, Power BI
• Good interpersonal and communications (verbal and written) skills, including the ability to effectively communicate with both business and technical teams.
• Proficiency in scenario analytics, mining for insights
• Prior experience in building machine learning models to improve active users for a product
• Prior experience in building models and managing model training, evaluations and integration with production systems
• Proficiency in Python, SQL and commonly used machine learning libraries to develop machine models, time series forecasting, etc.

Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.