<p><p>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.
</p><p><br/></p><p>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.<br/><br/>Your primary responsibilities will include :<br/><br/>- 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.<br/><br/>- 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).<br/><br/>- Partnering with business and architecture teams to translate complex, often ambiguous, business logic into robust, automated solutions.<br/><br/><b>Required Skills and Experience :</b><br/><br/>1.
<b>AI & Machine Learning Expertise : Generative AI & LLMs :</b> </p><p><br/></p><p>- Demonstrated, hands-on experience in applying Generative AI and Large Language Models to solve complex business problems.<br/><br/>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.
</p><p><p><b><br/></b></p><p><b>2.
Natural Language Processing (NLP) & Text Mining :</b></p><p><br/>- 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).<br/></p><br/><b>3.
Classical Machine Learning :</b> Strong foundation in applying traditional ML algorithms such as clustering, classification, decision trees, random forests, and support vector machines.<br/><br/><b>Data & Programming Skills : </b></p><p><b><br/></b></p><p><b>Data Processing and Wrangling :</b><br/><br/>- Extensive hands-on experience processing and wrangling both structured (e.g., BOMs, tabular data) and unstructured data from various formats, sizes, and storage mechanisms.<br/><br/><b>Programming Languages :</b> </p><p><br/></p><p>- 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.<br/><br/><b>Big Data & Cloud Technologies (GCP) :</b> </p><p><br/></p><p>- Experience working with large-scale datasets and cloud-based AI/ML platforms is essential.<br/><br/>- Proficiency with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, and Cloud Storage is highly & Problem-Solving Approach : Principles & Systems Thinking :</b> </p><p><br/></p><p>- 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.
</p><p><b><br/></b></p><p><b>Inquisitive and Tenacious Mindset :</b> </p><p><br/></p><p>- Excellent problem-solving skills, with a proven ability to challenge existing practices and ask "why" to uncover the logic behind established processes.
& Outcome-Oriented :</b> </p><p><br/></p><p>- 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.<br/></p><br/><b>Skills Required :</b><br/><br/>- LLM, GenAI, Machine Learning<br/><br/><b>Skills Preferred :</b><br/><br/>- Python, Big Query, Google Cloud Platform<br/><br/><b>Experience Required :</b><br/><br/>- 3+ years of hands-on experience in applying advanced machine learning and AI techniques, with demonstrated proficiency in the following areas :<br/><br/>1.
<b>Generative AI (GenAI) and Large Language Models (LLMs) :</b> 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.<br/><br/>2.
<b>Deep Learning :</b> Proficiency in deep learning principles, including the design and implementation of neural networks, reinforcement learning, and an understanding of transformer architectures.<br/><br/>3.
<b>Classical Machine Learning :</b> Strong foundation in traditional ML algorithms such as clustering, classification, decision trees, random forests, and support vector machines for predictive modeling and data analysis.<br/><br/><b>Experience Preferred :</b><br/><br/>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</p><br/></p> (ref:hirist.tech)