Unlike a standard AI role, we are looking for someone who can bridge two worlds. The project will be initially
front-loaded with traditional modeling
(statistical analysis, Bayesian techniques, time-series), but will quickly evolve into building
Agentic Systems
that incorporate these models as tools.
Non-Negotiable Requirements (Must-haves):
o
Experience:
At least 5+ years in AI/ML development and validation.
o
Traditional Modeling:
Deep expertise in statistical analysis (classification, regression, time-series, and Bayesian techniques). This is critical for the initial phase of the role.
o
GenAI & Orchestration:
Recent, hands-on experience building
Agentic systems
and orchestrating multiple AI agents to solve complex tasks.
o
Software Engineering:
Strong proficiency in Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow) and solid MLOps/DevOps practices.
o
Model Explainability:
Demonstrated experience with SHAP, LIME, and counterfactual explanations.
Key Differentiators:
o Master's or PhD in a quantitative field (Statistics, Applied Math, Computer Science, or Engineering).
o Practical experience with
Azure Databricks
.
o Experience integrating predictive models with optimization frameworks for prescriptive analytics.
Soft Skills:
We need a consultant-level profile-someone capable of identifying business opportunities, scoping data science solutions, and communicating effectively within a global team environment.
front-loaded with traditional modeling
(statistical analysis, Bayesian techniques, time-series), but will quickly evolve into building
Agentic Systems
that incorporate these models as tools.
Non-Negotiable Requirements (Must-haves):
o
Experience:
At least 5+ years in AI/ML development and validation.
o
Traditional Modeling:
Deep expertise in statistical analysis (classification, regression, time-series, and Bayesian techniques). This is critical for the initial phase of the role.
o
GenAI & Orchestration:
Recent, hands-on experience building
Agentic systems
and orchestrating multiple AI agents to solve complex tasks.
o
Software Engineering:
Strong proficiency in Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow) and solid MLOps/DevOps practices.
o
Model Explainability:
Demonstrated experience with SHAP, LIME, and counterfactual explanations.
Key Differentiators:
o Master's or PhD in a quantitative field (Statistics, Applied Math, Computer Science, or Engineering).
o Practical experience with
Azure Databricks
.
o Experience integrating predictive models with optimization frameworks for prescriptive analytics.
Soft Skills:
We need a consultant-level profile-someone capable of identifying business opportunities, scoping data science solutions, and communicating effectively within a global team environment.