Senior Data Scientist - Artificial Intelligence

Key Responsibilities:

- Develop and deploy advanced ML and deep learning models for forecasting, optimization, classification, and anomaly detection across supply chain and S&OP workflows.

- Build and operationalize predictive and prescriptive analytics solutions using techniques such as regression, clustering, time-series modeling, Transformers, reinforcement learning, and diffusion models.

- Design, prototype, and implement Generative AI and Agentic AI solutions (e. , GPT models, multi-agent workflows, AutoGPT/ReAct-style architectures).

- Work closely with supply chain stakeholders to convert business challenges into scalable data science solutions aligned with KPIs and operational goals.

- Build end-to-end ML pipelines, including data acquisition, feature engineering, model training, validation, deployment, and monitoring.

- Utilize cloud platforms (AWS/GCP/Azure), containerization tools (Docker), and MLOps practices for robust model deployment.

- Develop real-time and streaming analytics solutions using Kafka, Spark, or similar technologies.

- Apply NLP techniques to supply chain use cases such as contract interpretation, vendor communication analysis, and product/part classification.

- Continuously track new AI/ML advancements, including LLMs, agent frameworks, optimization techniques, and evaluate their applicability to supply chain automation.

- Communicate insights, model results, and complex analytical concepts clearly to technical and non-technical audiences.

Required Skills & Experience:

- 5+ years of hands-on data science experience, preferably in S&OP, supply chain, manufacturing, or logistics domains.

- Deep expertise in ML (regression, classification, clustering, time-series), deep learning (CNNs, RNNs, Transformers), and reinforcement learning.

- Proven experience with Generative AI, LLMs, diffusion models, and Agentic AI/multi-agent systems.

- Strong programming skills in Python and experience with ML frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost, Hugging Face, etc.

- Experience with AWS/GCP/Azure, Docker, and modern deployment pipelines.

- Strong business acumen with the ability to align models to supply chain KPIs and decision-making frameworks.

- Excellent communication skills with the ability to explain complex concepts to diverse stakeholders.

- Experience with real-time analytics and streaming data solutions (Kafka, Spark).

- Hands-on experience with LangChain, OpenAI API, or modern LLM agent architectures.

- Familiarity with optimization techniques (MILP, heuristics).

- Working knowledge of NLP applications in supply chain and S&OP