Data Science 2

Role: Data Scientist 2

Focus: Execution, model development, and refining existing pipelines.

Experience: 2–3 Years

Skillset

Modeling:

Proficiency in at least 2 modeling areas (Classification, Regression, Clustering, or Recommendation systems & embeddings).

ML/DL Stack:

Hands-on experience with Scikit-Learn, XGBoost / LightGBM and any of Deep Learning Libraries: PyTorch / TensorFlow.

Optimization:

Deep understanding of hyperparameter tuning and model evaluation metrics.

Engineering & Data:

Proficient in Python and writing complex SQL. Experience with Snowflake / Sagemaker is a plus.

Analytics:

Ability to translate daily metrics into actionable model adjustments.

Added Value:

Experience with MLflow, Model Registry or Weights & Biases for experiment tracking. Knowledge of LLM / SLMs.

Role Expectations

Primary Role: Building & Tuning

ML Areas: 2 Areas (Basic)

Deep Learning: Basics Cleared

Coding: Python / SQL

Testing: Validation Sets