We are seeking highly qualified and innovative Data Scientists to join our ambitious Product & Program Definition Transformation team. In this role, you will be central to developing the intelligent systems that power our move to a future-state PLM environment.

You will apply your expertise to solve complex, real-world problems at the heart of our engineering and business processes, directly contributing to the development of our Intelligent Transition Model and a suite of AI-Powered Accelerators.

Your primary responsibilities will include :

- Designing and building scalable AI/ML models to automate the decomposition and transformation of legacy artifacts (e.g., Program Direction Letters, Order Guides, BOMs) into the future-state data model.

- Developing analytics prototypes and accelerators that work on massive, diverse datasets to provide actionable insights for all project workstreams (e.g., VSM generation, relationship analysis, complexity metrics).

- Partnering with business and architecture teams to translate complex, often ambiguous, business logic into robust, automated solutions.

Required Skills and Experience :

1. AI & Machine Learning Expertise : Generative AI & LLMs :

- Demonstrated, hands-on experience in applying Generative AI and Large Language Models to solve complex business problems.

This includes expertise in advanced prompt engineering, model fine-tuning, and leveraging LLM APIs to automate the decomposition of complex business artifacts and unstructured text.

2. Natural Language Processing (NLP) & Text Mining :

- Proven ability to apply NLP and text mining techniques to extract structured information, rules, and relationships from unstructured or semi-structured documents (e.g., requirement documents, "author notes," technical specifications).

3. Classical Machine Learning : Strong foundation in applying traditional ML algorithms such as clustering, classification, decision trees, random forests, and support vector machines.

Data & Programming Skills :

Data Processing and Wrangling :

- Extensive hands-on experience processing and wrangling both structured (e.g., BOMs, tabular data) and unstructured data from various formats, sizes, and storage mechanisms.

Programming Languages :

- Strong proficiency in Python (including libraries like Pandas, NumPy) and flexibility to use other requisite languages and analytical tools as needed for the problem at hand.

Big Data & Cloud Technologies (GCP) :

- Experience working with large-scale datasets and cloud-based AI/ML platforms is essential.

- Proficiency with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, and Cloud Storage is highly preferred.

Mindset & Problem-Solving Approach :

First Principles & Systems Thinking :

- A proven ability to deconstruct complex legacy processes using a first-principles approach, focusing on understanding the root cause of inefficiencies rather than just treating symptoms.

Inquisitive and Tenacious Mindset :

- Excellent problem-solving skills, with a proven ability to challenge existing practices and ask "why" to uncover the logic behind established processes.

Collaborative & Outcome-Oriented :

- A strong team player who can work effectively with cross-functional teams and is driven to build practical, scalable solutions that deliver tangible business value.

Skills Required :

- LLM, GenAI, Machine Learning

Skills Preferred :

- Python, Big Query, Google Cloud Platform

Experience Required :

- 3+ years of hands-on experience in applying advanced machine learning and AI techniques, with demonstrated proficiency in the following areas :

1. Generative AI (GenAI) and Large Language Models (LLMs) : Proven expertise in leveraging GenAI, with hands-on experience in prompt engineering, model fine-tuning, and using LLM APIs for complex data processing, text mining, and automation.

2. Deep Learning : Proficiency in deep learning principles, including the design and implementation of neural networks, reinforcement learning, and an understanding of transformer architectures.

3. Classical Machine Learning : Strong foundation in traditional ML algorithms such as clustering, classification, decision trees, random forests, and support vector machines for predictive modeling and data analysis.

Experience Preferred :

3+ years of experience in at least one of the following languages : Python, R, MATLAB, SAS Experience with GoogleCloud Platform (GCP) including VertexAI, BigQuery, DBT, NoSQL database and Hadoop Ecosystem