Omni Inclusive
Position Title: Data Scientist
5 +Hands-on experience in
Python-based simulation modeling
(e.g., SimPy, AnyLogic (via Python), Pyomo, or custom frameworks). Proven experience in
predictive modeling
using libraries like scikit-learn, XGBoost, LightGBM, or TensorFlow. Strong understanding of
supply chain risk variables
specific to biopharma (e.g., lead time variability, manufacturing capacity constraints, regulatory delays). Experience working with time-series, probabilistic models, and scenario simulation. Strong knowledge of
statistical modeling ,
uncertainty quantification , and
Bayesian inference
is a plus. Experience working in cross-functional teams with domain experts in supply chain
Python-based simulation modeling
(e.g., SimPy, AnyLogic (via Python), Pyomo, or custom frameworks). Proven experience in
predictive modeling
using libraries like scikit-learn, XGBoost, LightGBM, or TensorFlow. Strong understanding of
supply chain risk variables
specific to biopharma (e.g., lead time variability, manufacturing capacity constraints, regulatory delays). Experience working with time-series, probabilistic models, and scenario simulation. Strong knowledge of
statistical modeling ,
uncertainty quantification , and
Bayesian inference
is a plus. Experience working in cross-functional teams with domain experts in supply chain