Data Scientist I or II; MAD-BS

Position: Data Scientist I or II (MAD-BS-OR)
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*
* Location:

**(HTA) NCP (Hillsboro, OR)
** Job :
** R0128931
* * Date Posted:
**** Company Name:
** HITACHI HIGH-TECH AMERICA, INC.
** Profession (Job Category):
** Data Analytics/Business Intelligence
*
* Job Schedule:

** Full time
** Remote:
** No
*
* 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., Tensor Flow, 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, Influx

DB)  + Analytical DBs (e.g., Click House, Postgre

SQL)  + 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 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…