Senior Data Scientist

Microsoft•Redmond, WA

13d•$119,800 - $261,000•Hybrid

About The Position

Microsoft Advertising (MSA) is seeking a Senior Data Scientist with expertise in Causal Inference, Measurement, Experimental design, Machine Learning, Econometrics, and Statistics. The Market Sciences Team within MSA utilizes massive-scale data to generate actionable insights, driving data-driven decisions across MSA in collaboration with cross-functional partners. This team leads model development, analytics, and experimentation in areas such as advertiser value and lifecycle, retention and churn, segmentation and forecasting, campaign effectiveness, ROI measurement, and demand health metrics. Their work involves creating measurement frameworks, conducting causal analyses, and developing algorithms to enhance sales and marketing impact. This role offers a unique opportunity to apply data science skills to significantly impact Microsoft's advertising business, its partners, and millions of end-users, working within a world-class, interdisciplinary team of data scientists, analysts, sales professionals, and product managers. The ideal candidate is curious, challenges the status quo, and develops data-driven solutions for ambiguous problems. Microsoft's mission is to empower every person and organization to achieve more, fostering a culture of growth mindset, innovation, and collaboration, built on values of respect, integrity, and accountability, creating an inclusive environment for all.

Requirements

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 techniques and reporting results)
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 techniques and reporting results)
OR equivalent experience.
Experience in all phases of managing data science projects including problem definition, solution formulation, model building, productionizing and delivering measurable impact.
Hands-on experience in design & problem-solving skills with programming languages, such as Python and R and SQL-like query languages.
Experience in applying statistics, designing experimentation, causal inference and metrics.

Nice To Haves

Doctorate 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 techniques and reporting results)
OR Master'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 techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Responsibilities

Design metrics to measure and track Microsoft advertiser demand health and inform/guide sales and marketing execution.
Quantify the impact and incrementality of various sales and marketing programs.
Design and analyze the results of online and offline experiments.
Use quasi-experiments and counterfactuals to understand causality in scenarios where AB testing is not feasible.
Prototype algorithms for creating, managing, and optimizing demand generation activities through sales, marketing, and product to support the ad marketplace.
Work with key business stakeholders to understand underlying business needs and formulate them into discrete, manageable problems with well-defined measurable objectives and outcomes.
Develop new predictive and prescriptive models using advanced statistical and machine learning techniques with a goal of productionizing solutions.
Influence stakeholders to make product/service improvements that yield customer/business value by effectively making compelling cases through storytelling, visualizations, and other influencing tools.