Data Science Lead

**About Data Science Lead Role**:
An Individual contributor role. As the Data Science Lead, you will be a part of AE’s global supply chain function. Within the Supply Chain Planning function, you will support the specific data and analytics needs as the function is heading toward its digital transformation. As a highly motivated Data Scientist, you will aid in solving complex supply chain problems using optimization & graph techniques. You will support internal teams in moving away from old working methods and mining insights. You will get an excellent chance to understand the supply chain function in detail from the professionals and opportunities to learn and grow in Supply Chain Analytics space. The Data Science Lead is expected to work closely with key stakeholders and possesses the relevant technical skills required to implement data science solutions that enable the use of data as a strategic asset.

**Responsibilities**
- Engage with stakeholders (operational managers, senior executives) to understand the critical business question addressed through analytics.
- Lead discovery sessions and requirements workshops for business users and use business and information technology tools to evaluate in-scope value streams, business processes, or procedures where needed.
- Play a key role in driving detailed technical project objectives and execution management, architecture design, and code reviews, demonstrating technical leadership.
- Manage end-to-end Machine learning projects lifecycle.
- Drive end-to-end Proof of value initiatives and implement (Productionize) the pilot programs selected by the senior executives.
- Support Proof of value initiatives with internal or external partners or vendors.
- Engage with global research, industry, and standards development communities to identify and implement new technologies and best practices
- Guide the team of data analysts, data scientists, and interns with effective leadership to build robust data capabilities
- Drive & develop in-house data literacy programs (Basic & advance)

**Requirements**:
**Essential**
- Minimum 6 years of experience in a related field, such as programming, statistics, data science, or equivalent experience (Data Science, Mathematics, Statistics, Information Engineering, Computer Science, or similar)
- Proven experience with Python and delivery of production-grade code
- Proven experience in Machine Learning, Natural Language Processing & Graphs technologies)
- Experience with Machine learning operation end-to-end life cycle
- Experience working with senior business stakeholders

**Desirable**
- Hands-on experience with analytics, machine learning, and statistics in a commercial environment.
- Experice to advanced analytics algorithms and tools such as GNN, LSTMs, Auto-encoders, LLMs (such as GPT-4), Graph NN’s
- Familiarity with PyTorch, MLFlow, Great Expectations, Tableau, Neo4j or Arango DB, or Cosmos DB
- Working experience on Azure or Google Cloud service for Machine learning and Data Engineering.
- Knowledge of SAP and relevant data structure, extraction, preparation, and visualization tool. (e.g., SAP BW)
- Good familiarity with data governance, master data, and metadata management.
- Experience with open-source data & analytics tools.
- Preferably with experience in Manufacturing or Supply Chain

**Learning & Development Opportunity**
- You will get the opportunity to learn and grow in Supply Chain Digital Transformation space as AE has just started its journey.
- Learning and growth of the cloud platforms and internal coaching & mentoring from the Analytics Leaders in the space.