Experience Mandatory Skills Work Location Data Scientist
PySpark & Databricks
Classical ML experience (e.g., TensorFlow, H2O) and data science libraries (e.g., Spark, ML)
Graph Data science knowledge (should have done community detection, path analysis, community analysis)
11 to 17 Years Primary Chennai, JD Details
Databricks/PySpark with classical ML experience. They CANNOT be just package runners who are stuck in the weeds, without any understanding of the business goals or value expected from the exercise.
They must have been through the full ML process – exploratory data analysis, model selection, training, validation, tuning, deployment. Classical ML techniques like regression, classification, clustering, deep learning is all par for the course.
They must also have Graph data science knowledge (e.g. they should have done community detection, path analysis, community analysis) – using iGraph / network etc. Knowledge of Neo4J, Cypher is a bonus.
We don't do NLP in my team.
They must know Databricks/Pyspark – this is our core toolset.
Regarding visualization – NOT looking for dashboard developers. Any data scientist needs to at least have some static charting & visualization capabilities as part of EDA (exploratory data analysis) to detect visual patterns, validate hypothesis or simply check for correlations. Typical packages we use here are Seaborn, Matplotlib just to give you an idea. I'm not wedded to these packages – any are fine if they can visualize the data.
They need to be self-driven, self-managed and delivery oriented – mature enough to make progress without too much handholding.
