Data Scientist
Core
Build, validate, and deploy machine learning models and pipelines to translate business problems into actionable insights from large structured and unstructured datasets.
Role type
Senior IC Data Scientist (ML Engineering)
Builds
Predictive analytics models, automation pipelines, and data visualizations for business stakeholders.
Domain
Enterprise IT services, digital transformation, cloud infrastructure.
Deliverable
production ML models | dashboards & analysis
Required skills
Python (pandas, scikit-learn, NumPy), SQL, supervised/unsupervised learning, time series forecasting, hypothesis testing, feature engineering, Spark, Docker, Kubernetes, MLflow, Power BI/Tableau
Preferred skills
NLP, GenAI/LLMs, recommendation systems, MLOps (Kubeflow, Airflow)
Technologies
AWS (SageMaker, Redshift), GCP (Vertex AI, BigQuery), Azure (ML Studio), MongoDB, Cassandra, BigQuery, Redshift, Snowflake, Git, Jira, Confluence
Responsibilities
Analyze large volumes of structured and unstructured data to extract meaningful insights. Build, validate, and deploy machine learning models for predictive analytics and automation. Design and implement machine learning pipelines for structured and unstructured data. Build dashboards and data visualizations to communicate findings effectively. Conduct testing, hypothesis validation, and experiment tracking. Continuously monitor model performance and retrain based on data drift and feedback loops.
Seniority
Senior, hands-on IC
