Senior Data Scientist

Market Sciences Team in MSA is hiring talented, highly motivated and productive individuals with expertise in the areas of: Computer Science, Machine Learning, Econometrics, Statistics, Modeling, Simulation and Data Mining. The team develops and applies advanced techniques to turn our petabytes of data into insights; and to drive actions based on those insights. The team works closely with partners across MSA to enable rigorous, effective, and data-driven decision making. Some examples of the challenges we face:

• Modeling the dynamics of the paid search market.
• Understanding Advertiser value, lifecycle, opportunity, and marketing objectives.
• Designing metrics to measure and track Microsoft advertiser demand health and inform/guide sales and marketing execution.
• Designing and analyzing the results of online and offline experiments. Using quasi-experiments and counterfactuals to understand the causality in scenarios where AB testing is not feasible.
• Prototyping algorithms for creating, managing, and optimizing demand generation activities through sales, marketing, and product to support our marketplace.
• Defining metrics and building a measurement framework to quantify the impact and incrementality of various sales and marketing programs.

As a Senior Data Scientist in Market Sciences Team, you will have the opportunity to apply your data science skills to have a real impact on Microsoft’s business, our advertising partners, and millions of end users. This role is a unique opportunity to work with a world-class, interdisciplinary group of data scientists, analysts, sales and product managers.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required Qualifications:

• Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techn
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical tec
  • OR equivalent experience.
• 2+ years experience in all phases of managing data science projects including: problem definition, solution formulation, model building, productionizing and delivering measurable impact.
  
• 2+ years of extensive experience in statistical analysis, machine learning, and data mining
• Proficiency in least one of the programming languages like Python/R/SQL

Preferred Qualifications:

• Ability to work independently and collaboratively in an interdisciplinary team environment.
• Prior working experience within online advertising is a plus

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $153,600 - $250,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until December 13, 2024. 

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

• Work with key business stakeholders to understand the underlying business needs and formulate the needs into discrete, manageable problems with well-defined measurable objectives and outcomes.
• Transform formulated problems into implementations plans for experiments by defining success metrics, applying/creating the appropriate methods, algorithms, and tools, as well as delivering statistically valid and reliable results.
• Acquire the data necessary for your project and develop usable data sets for modeling.
• Develop new predictive and prescriptive models using advanced statistical and machine learning techniques with a goal of productionizing solutions.
• Evaluate your team’s models and recommend improvements as necessary, drive best practices for models, and develop operational models that run at scale. Conduct thorough reviews of data analysis and modeling techniques, and identify and invent new evaluation methods
• Influence stakeholders to make product/service improvements that yield customer/business value by effectively making compelling cases through storytelling, visualizations, and other influencing tools.
• Research and maintain a deep knowledge of the industry, including trends and technologies, so that you can identify and analyze the applicability and scalability of innovative data science methods.