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Data Science Engineer at Microsoft
Hyderabad, Telangana, India -
Full Time

Start Date

Immediate

Expiry Date

28 Feb, 26

Salary

0.0

Posted On

30 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, Machine Learning, Python, SQL, ML Frameworks, Cloud Platforms, Big Data Technologies, Statistical Modeling, Predictive Analytics, Experimentation Design, Communication, Stakeholder Management, AI Tools, Continuous Learning

Industry

Software Development

Description
Design and implement advanced analytics solutions to support commerce data platform initiatives including analytics based on Machine Learning Models. Partner with engineering and product teams to define data requirements and ensure high-quality data pipelines. Conduct exploratory data analysis, feature engineering, and model evaluation using structured and unstructured datasets. Ensure the models built are operable, scalable, extensible and performant. Develop dashboards, visualizations, and storytelling artifacts to communicate insights to stakeholders. Lead experimentation efforts to evaluate new features, forecasting, data quality and anomaly detection systems. Build extensible solutions on LLM models to improve productivity of engineers across the commerce organization. Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or related field. 2+ years of experience in data science, analytics, or applied machine learning. Proficiency in Python, SQL, and ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with cloud platforms (Azure preferred) and big data technologies. Strong understanding of statistical modeling, predictive analytics, and experimentation design. Excellent communication and stakeholder management skills. Demonstrated experience leveraging AI tools and technologies to enhance engineering effectiveness, coupled with a strong curiosity and commitment to continuous learning in the field of Artificial Intelligence.
Responsibilities
Design and implement advanced analytics solutions for commerce data platform initiatives. Partner with engineering and product teams to define data requirements and ensure high-quality data pipelines.