Data & Applied Scientist

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As a Data & Applied Scientist on our team, you will apply advanced AI, machine learning and data science techniques to solve high-impact problems. You will experiment with large-scale datasets, develop and evaluate predictive models and evaluation metrics, and collaborate closely with engineers and product partners to integrate these solutions into services. This opportunity will allow you to accelerate your career growth, deepen your expertise in cloud-scale AI/ML, and directly shape the future of AI-powered services on a global scale. We also support flexible work arrangements, including partial or fully remote work options.

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
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND experience in data-science (e.g., managing structured and unstructured data, applying statistical tec
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND experience in data-science (e.g., managing structured and unstructured data, applying statistical tec
  • OR equivalent experience.
• Experience customer-facing, project-delivery experience, professional services, and/or consulting experience.

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

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

Preferred Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science,
  • OR related field AND experience in data-science (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 experience in data-science (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 experience in data-science (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.

#DataScience #MachineLearning #AI #AzureML #Microsoft #MicrosoftInEstonia #MDCE

• Data Acquisition & Exploration – Understand where to gather the data needed for projects and use querying, visualization, and reporting techniques to explore and describe that data.
• Model Development & Evaluation – Develop machine learning models using appropriate techniques and tools, and evaluate outputs for statistical and business significance, refining models based on customer feedback.
• Coding Best Practices – Write efficient, well-structured code and follow software engineering best practices (version control, code reviews, testing) to build secure, reliable machine learning solutions.
• Customer Focus – Ensure solutions address customers’ business goals and real-world needs; communicate progress clearly to manage expectations and deliver actionable insights.
• Cross-Functional Collaboration – Collaborate with researchers, software engineers, and product managers (PMs) to design, develop, and deploy machine learning features and services; gather requirements, document designs, conduct code reviews, and ensure smooth handoffs between teams.
• Deployment & Operations – Deploy trained models to production and integrate them with cloud services to ensure scalability and reliability; set up metrics and alerts to monitor performance, troubleshoot issues, and participate in on-call rotations to maintain system stability.
• Continuous Improvement – Continuously experiment with new techniques to improve model performance and integrate the latest advancements in artificial intelligence and machine learning (e.g., large language models, natural language processing) into our solutions; stay up-to-date with emerging research and share insights to keep the team at the cutting edge.