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

Job description

Job Description

POSITION: Data Scientist I or II DIVISION: Metrology and Analysis Systems Division (MAD)

COMPANY

Hitachi High-Tech America, Inc. (“HTA”)

TRAVEL

Up to 5% (internationally)

REMOTE WORK

Hybrid (+50% Remote) – Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136,961 annually Data Scientist II: $121,673 - $167,301 annually This pay range is for the position’s base pay only. This position may be eligible for other compensation including bonus pay and/or allowances. Candidates will receive additional information during the interview and selection process.

Position Level

The best fit candidate selected for this position will be offered a job title/level (Data Scientist I vs. Data Scientist II) that is most appropriate after evaluating the person's education, experience, training, knowledge, skills, and abilities.

POSITION SUMMARY

Data Scientists are responsible for the development and maintenance of Artificial Intelligence (AI) software and systems for Hitachi High-Tech America, Inc. (HTA) products.

PRIMARY RESPONSIBILITIES

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 EDUCATION, LICENSES, and/or CERTIFICATION

REQUIREMENTS

Master of Science degree in Data Science, Statistics, Computer Science, or similar quantitative field EXPERIENCE and TRAVEL

• 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 Equal Opportunity Employer (EOE) Hitachi High-Tech America, Inc. is an equal opportunity employer.

Hitachi High-Tech America, Inc. is committed to equal employment opportunities for qualified applicants without discrimination on the basis of actual or perceived of race (including traits historically associated with race, such as natural hairstyle), color, national origin, ancestry, religious creed, age, sex, sexual orientation, gender (including gender expression and gender identity), marital status, registered domestic partner status, family status, military and veteran status, domestic violence victim status, medical condition (including genetic characteristics), physical or mental disability, pregnancy, or any other legally protected characteristic or status.

If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to [email protected]