Data Scientist I or II (MAD-BS-OR)

Data Scientists are responsible for the development and maintenance of Artificial Intelligence (AI) software and systems for Hitachi High-Tech America, Inc. (HTA) products., * Hands-on development and write algorithms in machine learning, statistical modelling, neural nets, and pattern recognition from data exploration

• Develop, train, and deploy ML models for Time-series forecasting and anomaly detection. Classification and regression on tabular and sensor data, predictive maintenance and failure prediction
• Design end-to-end ML pipelines including Data ingestion, feature engineering, model training, evaluation, and deployment
• Lead and support Root Cause Analysis (RCA) investigations using data-driven approaches
• Build frameworks for Fault Tree Analysis (FTA) and failure mode identification
• Collaborate with domain experts (engineering, operations) to translate failure patterns into ML features and models
• Design and develop Agentic AI systems capable of:
• Autonomous reasoning over structured and unstructured data
• Tool usage (query engines, APIs, analytics pipelines)
• Multi-step decision making and diagnostics workflows
• Implement LLM-based systems with:
• Tool-calling frameworks
• Retrieval-Augmented Generation (RAG)
• Structured outputs and validation pipelines
• Partner with cross-functional teams (Data Engineers, Software Engineers, Domain Experts)
• Build scalable, production-ready solutions using:
• Python-based ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Data processing tools (Pandas, Spark, SQL)
• Deploy models and services using:
• REST APIs (FastAPI, Flask)
• Containerization (Docker, Kubernetes)
• Work with modern data platforms:
• Time-series DBs (e.g., Prometheus, InfluxDB)
• Analytical DBs (e.g., ClickHouse, PostgreSQL)
• Vector DBs (e.g., Qdrant, FAISS)
• Translate business problems into technical solutions
• Creating architecture and complex designs independently and documenting them
• Integrate and test software to confirm compliance with specifications
• Developing functional specifications
• Participate in design reviews, code reviews of peers and test reviews
• Performing functional tests
• Other duties as assigned

• Master of Science degree in Data Science, Statistics, Computer Science, or similar quantitative field

EXPERIENCE And TRAVEL REQUIREMENTS

• Must have at least five (5) years of practical experience in writing algorithms in Machine Learning, Statistical Modelling, Neural Nets, and Pattern Recognition from data exploration
• Five (5) years of experience in Data Science / Machine Learning
• Strong programming skills in Python
• Proven experience with:
• Time-series analysis and anomaly detection
• Statistical modeling and machine learning algorithms
• Hands-on experience with:
• Root Cause Analysis (RCA)
• Fault Tree Analysis (FTA) or failure modeling
• Experience working with real-world, noisy, and large-scale datasets
• Experience with Agentic AI / LLM systems, including:
• Tool-calling architecture
• RAG pipelines
• Prompt engineering and evaluation frameworks
• Familiarity with:
• Distributed systems and scalable ML infrastructure
• MLOps practices (CI/CD, monitoring, model versioning)
• Knowledge of:
• Signal processing or physics-based modeling
• Graph-based reasoning or causal inference
• Full software development lifecycle experience, must be comfortable working using Agile as well as iterative methodologies
• Experience with Test-driven development using tools to spot performance issues and memory leaks.
• This position requires international travel for business purposes - up to 5%

SKILLS And ABILITIES REQUIREMENTS / SAFETY REQUIREMENTS

• Ability to investigate and apply new technologies
• Effective oral and written communication skills, including ability to effectively communicate challenging or technical concepts.
• Excellent relationship building skills
• General technical knowledge of semiconductor metrology equipment
• Strong engineering analytical and problem-solving skills
• Proactively undertake R&D activities and deliver tangible results under deadlines
• Ability to manage multiple tasks and prioritize work accordingly
• Work longer than normal hours as needed during releases and customer escalations
• Self-sufficient, self-reliant, and self-disciplined, but also able to operate effectively as part of a team
• Ability to comprehend and enforce safety policies