Are you passionate about applying your knowledge of statistics, machine learning and natural language processing to solve big problems? Are you interested in driving data-based decisions to tackle strategic challenges? We are looking for someone to do just that in the context of Microsoft’s biggest asset – its people.
One key strategic people challenge at Microsoft is exploring the complex interplay between the multifaceted aspects of employee productivity and the equally rich dimensions of the lived employee experience. Engineering Thrive is Microsoft’s implementation of understanding productivity through the SPACE and Thriving frameworks and is driven by a team crossing both Human Resources (HR) and Engineering, supported by Microsoft senior leadership.The Data and Applied Science
team within Microsoft’s People Analytics organization, HR Business Insights (HRBI),
is seeking a Senior Data Scientist
with experience leveraging machine learning and natural language processing techniques to create scalable, impactful insights from both structured and unstructured data. A well-qualified candidate is highly technical and possesses the patience and persistence needed to see complex problems through to resolution.
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.Responsibilities
- Build, maintain, and improve end-to-end machine learning pipelines and solutions that deliver insights at scale from both structured and unstructured data.
- Writing clear, efficient code for multiple features, with expertise in modelling, coding, and debugging.
- Using your data science expertise to identify factors that influence project outcomes.
- Proficiency in data engineering concepts like MLOps, Apache Spark, Docker, AML, Azure OpenAI, and REST API development.
- Serve as a subject matter expert on advanced analytics, partnering with other teams to apply and leverage this skillset to guide data-driven decision making.
- Collaborate closely with other data scientists, analysts, Engineering business partners and HR clients connected with Engineering Thrive project team.
- Contract with co-workers, partners and customers to define data needs, research questions, analysis plans, and deliverable timelines.
- Translate complex technical findings into succinct, actionable business insights, often in coordination with partners who help you tell a holistic story.
- Occasionally support high priority ad hoc requests from company and HR leadership.
- Passion for innovation and discovering new insights into people analytics leveraging advanced machine learning and Natural Language Processing (NLP) techniques.
- Self-directed learner in the ever-advancing space of machine learning, deep learning, and text analytics.
- Embody our culture and values
Additional Or Preferred Qualifications
- Doctorate in Data Science, Mathematics, Statistics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., hands-on experience with structured and unstructured data, applying statistical, machine learning and deep learning techniques)
- 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, Operations Research, Computer Science, or related field AND 5+ years data-science experience
- OR equivalent experience.
- 3+ years of hands-on experience with Python, R and SQL
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
- OR Master's Degree in Data Science, Mathematics, Statistics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience
- OR equivalent experience.
- Proficiency in ML tools & frameworks such as Jupyter notebook, Scikit-Learn, Azure, AI/ML/Cognitive Service, Spark, TensorFlow, PyTorch, etc.
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $112,000 - $218,400 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 $145,800 - $238,600 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 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.