Senior Data Scientist
- Manages data collection and preparation for projects. Handles data engineering also for production code.
- Applies machine learning solutions and algorithms to achieve objectives , prepare and evaluate data, and communicate findings and risks. Writes scripts in various languages and understands Microsoft AI and ML tools. Designs experiments and operationalizes models at scale. Coaches junior engineers on best practices.
- Understands relationship between selected models and business objectives . Ensures clear linkage between selected models and desired business objectives . Defines and designs feedback and evaluation methods. Coaches and mentors less experienced engineers as needed. Presents results and findings to senior customer stakeholders.
- Drive the development and adoption of Responsible AI practices, ensuring ethical, transparent, and compliant use of AI systems.
- Provides feedback, coaching, and support to engineering team and other teams based on business knowledge, technical expertise , and industry trends.
- Demonstrates excellent coding and debugging skills across multiple features/solutions.
- Leads data-driven projects with business acumen and data science expertise .
- Drives business value by collaborating with stakeholders and improving solutions.
- Delivers customer-oriented solutions and builds trust with Microsoft products.
- Design and maintain scalable ML pipelines, feature stores, and training/inference systems to ensure reliable, high-performing models in production .
- Manage the full ML lifecycle-deployment, monitoring, retraining, CI/CD, and governance-for scalable, reliable, and compliant s olutions.
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND relevant 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 relevant 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 relevant years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
- Customer-facing, project-delivery experience, professional services, and/or consulting experience.
- Proficient in Python with experience in Pandas, Scikit-learn, and the Python ML stack; strong coding skills for developing and maintaining machine learning models.
- Enjoy travel and are comfortable with travel up to 25%
- This role requires to have or be able to obtain SC clearance in the future.
- Proficient in additional programming languages such as C#, Java, and C/C++.
- Skilled in building and maintaining models in various domains, including computer vision, forecasting, recommendation systems, and NLP.
- Experienced with agile development practices and Git version control.
- Familiar with deep learning frameworks like TensorFlow or PyTorch ; experience with GenAI /LLMs is a plus.
- Experienced in the operational aspects of machine learning, including deployment, monitoring, and continuous integration of ML models.
- Relevant years of experience working with customers.
- Expertise in domains such as financial services, retail, marketing, healthcare, manufacturing, media, or telecommunications.
- Effective at communicating technical models in business and technical contexts.
- Comfortable with regional travel up to 25%.
- Familiarity with Spark, SQL, Graph stores, or NoSQL stores is helpful.
- MS or PhD in Computer Science, Electrical Engineering, Statistics, Operations Research, or an equivalent technical field.
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