Apeiro Digital builds health data platforms for governments and healthcare organisations around the world. Our data team turns large-scale health data into real-time analytics, forecasting and decision intelligence across all our products.
About the role
This role sits at the intersection of data engineering and applied data science. You will own both the production pipelines and the models that run on top of them.
What you will do
Build and run production Python services and APIs that serve analytics and machine learning outputs at scale
Design ETL and ELT pipelines feeding analytical and machine learning workloads
Develop predictive and statistical models for health and operational use cases such as demand forecasting and population health
Own model monitoring, retraining and data quality, not just the first deployment
Extend our lakehouse built on Apache Iceberg,
ClickHouse and Parquet, with Dagster orchestration and dbt transformations
Write clean, tested, production-grade code, not notebooks handed off to engineering
What we are looking for
6 to 9 years of experience with a real split between data science and backend or data engineering
Solid Python (non-negotiable): Pandas, NumPy, scikit-learn, SQLAlchemy, FastAPI or similar
Solid SQL and hands-on work with analytical databases (ClickHouse preferred; BigQuery, Snowflake or DuckDB accepted)
Models you have shipped to production and maintained yourself
Kafka or event-driven architecture is a robust plus
Health data experience (for example FHIR) is a differentiator, not a requirement
📌 Senior Data Scientist Noida
🏢 Apeiro
📍 Noida
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