Description
& Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics.Responsibilities:
About the Role: We are looking for a highly skilled Data Scientist who can work across the entire data science lifecycle—from feature engineering and model development to deployment and monitoring—using modern ML platforms.
The ideal candidate will have hands-on experience with Azure Machine Learning, Databricks, and MLflow, and will be comfortable building scalable solutions for real-world business problems.
What will you do: Data Preparation & Feature Engineering · Collect, clean, and preprocess structured and unstructured data from multiple sources.
· Perform feature selection, transformation, and creation for optimal model performance.
Model Development · Design, train, and validate predictive and prescriptive models using advanced statistical and machine learning techniques.
· Experiment with algorithms for classification, regression, clustering, and NLP.
Model Deployment & Monitoring · Deploy models into production using MLflow and Azure ML pipelines.
· Implement model versioning, reproducibility, and automated retraining strategies.
End-to-End ML Lifecycle Management · Manage experiments, track metrics, and maintain model registry in MLflow.
· Ensure compliance with MLOps best practices for scalability and reliability.
Collaboration & Communication · Work closely with data engineers, business analysts, and stakeholders to translate business requirements into data-driven solutions.
· Present insights and recommendations through dashboards and reports.
Mandatory skill sets:
‘Must have’ knowledge, skills and experiences Technical Expertise · Strong proficiency in Python (pandas, scikit-learn, PySpark) and SQL.
· Experience with Azure Machine Learning, Databricks, and MLflow.
· Solid understanding of MLOps principles and CI/CD for ML models.
Data Science & ML · Hands-on experience in feature engineering, model selection, hyperparameter tuning.
· Familiarity with deep learning frameworks (TensorFlow, PyTorch) is a plus.
Cloud & Big Data · Knowledge of Azure services like Azure Data Lake, Azure Fabric, and Azure Functions.
· Experience working with large-scale data on distributed systems.
Soft Skills · Strong problem-solving and analytical skills.
· Excellent communication and stakeholder management abilities.
Preferred skill sets:
‘Good to have’ knowledge, skills and experiences · Familiarity with data lake architectures and delta lake concepts · Familiarity with Azure ML/Databricks ML
Years of experience required: · 5-8 years
Education qualification:
o BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)
Education Degrees/Field of Study required: Master of Engineering, Bachelor of EngineeringDegrees/Field of Study preferred:Certifications Required Skills Microsoft Azure, Python (Programming Language)Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}Desired Languages Travel Requirements Available for Work Visa Sponsorship?