Data Scientist

Foxconn-PCE Technology•Milwaukee, WI

About The Position

Foxconn provides innovative design and advanced manufacturing capabilities through AI-driven solutions. As a global leader in technology services and smart manufacturing, Foxconn is expanding across electric vehicles, digital health and robotics, underpinned by core strengths in artificial intelligence, semiconductors and next-generation communications to enable smart manufacturing, smart EV and smart city platforms. AFE, Inc., a Foxconn company, is currently seeking a Data Scientist to join our Smart Manufacturing Platform-industrial AI (SMP-iAI) team in Milwaukee, WI. This role focuses on designing, developing, and deploying data science and GenAI solutions for factory and industrial applications. You will work closely with product, platform and software teams to translate real-world manufacturing use cases into robust, scalable AI capabilities on our Smart Manufacturing Platform.

Requirements

Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering or a related field required; Master’s degree preferred.
2–5 years of recent, hands-on experience in data science and machine learning, including delivering models or analytics solutions into production or business use.
Strong foundation in core ML techniques (regression, classification, clustering, time-series, deep learning; supervised and unsupervised methods) and experience applying them to real business problems.
Practical experience with generative AI and large language models, such as prompt engineering, fine-tuning or adapting foundation models, building chat/assistant workflows, or RAG-style applications.
Proficiency in Python for data science and ML (e.g., pandas, NumPy, scikit-learn; plus PyTorch or equivalent).
Solid understanding of data engineering and storage technologies, including SQL and NoSQL databases and data pipeline/ETL concepts.
Strong analytical and problem-solving skills, with the ability to design experiments, interpret complex results, and drive decisions using data.
Team-oriented mindset and demonstrated ability to collaborate with distributed, cross-functional teams, with excellent written and verbal communication skills.

Nice To Haves

Experience with big data frameworks or streaming data is a plus.
Familiarity with modern software development practices (Git, code review, testing, CI/CD) and with web/API concepts (RESTful services, basic HTML/CSS/JavaScript) is preferred.
Experience working with cloud platforms and, ideally, GPU-accelerated environments for deploying AI models, is a plus.

Responsibilities

Design, build and maintain end-to-end data science and GenAI solutions for manufacturing use cases, from problem framing and data exploration through model development, validation, deployment and monitoring.
Develop and operationalize GenAI and LLM-based applications for industrial scenarios, such as: Natural-language copilots for process engineers and operators to query production, quality and equipment data;
Work-instruction and SOP assistants that summarize and personalize procedures by product, line or station;
Root-cause and anomaly analysis assistants that explain out-of-control conditions and suggest likely causes;
NL-driven maintenance and quality-report generators that transform logs and sensor data into clear narratives.
Implement natural-language–based data analytics and data modeling workflows that convert user questions into reproducible analyses (e.g., auto-generated SQL / queries, model runs, dashboards) and return interpretable results aligned with KPIs such as yield, scrap, downtime and OEE.
Work with structured and unstructured data from diverse factory and enterprise sources (MES, ERP, sensor/IoT data, images, PDFs and logs), including data ingestion, cleaning, feature engineering and data quality checks.
Build and refine GenAI workflows including prompt design, retrieval-augmented generation (RAG), vector search, tool-calling and guardrails, with a focus on safety, reliability, latency and explainability in production settings.
Collaborate with software engineers and architects to integrate ML and GenAI models into backend services and the Smart Manufacturing Platform, supporting API design, performance tuning and lifecycle management.
Participate in planning and roadmap discussions for AI initiatives: help define scope, technical approach, success metrics, data requirements and deployment plans across multiple plants and product lines.
Create clear documentation, technical reports and reusable code artifacts so that solutions can be supported, scaled, and transferred to other teams or sites
Engage with cross-functional stakeholders (manufacturing, operations, quality, IT, business teams) to understand needs, prioritize opportunities and present findings and recommendations to both technical and non-technical audiences.
Stay current with advancements in data science, machine learning and GenAI (models, frameworks, tooling, MLOps/LLMOps) and share best practices within the team.
Perform other duties and responsibilities as required or requested.