Senior Data Scientist (Local to Charlotte NC)

Senior Data Scientist (Local to Charlotte NC)

BERTRANDT US INC - 3.5

Charlotte, NC Job Details Contract $122,000 - $175,000 a year 1 hour ago Benefits Paid holidays Disability insurance Health insurance 401(k) Qualifications AI models TensorFlow Data model design Search engines Databricks Data modeling projects PyTorch Team leadership Spark Amazon SageMaker Generative models AI platforms (beyond public GPTs) Scalable systems Computational framework Prompt engineering SQL Machine learning cloud services Machine intelligence Developing large-scale AI models Cloud Native Design Scalability Distributed computing Machine learning libraries Machine learning frameworks Feature engineering Generative AI Database software proficiency

Full Job Description Description:

Ready to drive the future? As part of the global Bertrandt Group, our team of innovators tackles cutting-edge projects across ADAS, Autonomous Driving, Electric Mobility, and Manufacturing Support, transforming complex issues into sustainable, connected solutions. With the strength of a global network of over 14,500 colleagues in 50+ locations, Bertrandt US combines deep expertise in Electronics, Product Engineering, Physical, and Production & After Sales. Join us in engineering tomorrow's mobility today.

General Benefits:

Complete and comprehensive benefits package including Med/Dent/Vision Employer paid STD/LTD/Life 401k Retirement program Generous paid vacation/sick/holidays Creativity encouraged in a fun, friendly work environment __________________________________________________________________________________________________________________________________

• Long term contract
• This position can be hybrid-remote (in office 2-3 days)
• Start date is approximately 6/8/26
• Local candidates preferred, due to upcoming/immediate start date
• Data Engineering & Data Processing Design and develop scalable ETL/ELT pipelines for ingesting, transforming, and processing structured and unstructured data.

Build and optimize data pipelines using Databricks, Spark, SQL, and cloud-native AWS services. Implement data quality, validation, lineage, and monitoring processes. Support medallion/lakehouse architecture patterns including bronze, silver, and gold data layers. Develop data pipelines to support AI/ML, GenAI, and RAG workloads, including document ingestion and embedding generation workflows. Machine Learning & Modeling Design and implement scalable ML models for classification, regression, clustering, forecasting, and recommendation systems. Apply advanced techniques including deep learning, ensemble learning, NLP, Generative AI, and LLM-based solutions where applicable. Conduct model evaluation, tuning, validation, and performance optimization using industry best practices. Develop and train models within Databricks ML and/or AWS SageMaker leveraging distributed computing and scalable cloud infrastructure. Build reusable feature engineering and model training pipelines. Develop Retrieval-Augmented Generation (RAG) solutions integrating LLMs with enterprise knowledge sources and vector databases. Cloud & MLOps Deploy and manage ML and GenAI models using AWS SageMaker and Databricks, including endpoint configuration, monitoring, and retraining workflows. Utilize Databricks MLflow for experiment tracking, model registry, and deployment automation. Implement and support vector database solutions for semantic search and RAG architecture. Collaborate with DevOps and platform teams to implement CI/CD pipelines for ML, GenAI, and data workloads. Automate operational workflows and optimize cloud resource utilization, scalability, reliability, and security. Deliverables Production-ready ML and GenAI solutions with supporting technical documentation. Scalable ETL/ELT pipelines and curated datasets. End-to-end Databricks notebooks, jobs, and workflows. Feature engineering pipelines and reusable ML components. RAG pipelines integrated with vector databases and enterprise knowledge sources. Weekly status reports and participation in Agile sprint ceremonies.

Requirements:

Skills & Qualifications 8+ years of experience in Data Science, Machine Learning, and Data Engineering. Strong proficiency in Python, SQL, Spark, and ML libraries such as scikit-learn, TensorFlow, and PyTorch. Experience with Generative AI, LLM frameworks, prompt engineering, and RAG architecture. Hands-on experience with vector databases and semantic search technologies. Hands-on experience with Databricks, MLflow, Delta Lake, and AWS SageMaker. Experience designing scalable data pipelines and distributed data processing solutions. Strong understanding of data mining, feature engineering, and data modeling techniques. Experience with cloud-native AWS data services and orchestration frameworks. Excellent communication, collaboration, and leadership skills.

EEO-Statement:

Bertrandt US is committed to fostering an inclusive and diverse workplace. We provide equal employment opportunities to all employees and applicants and strictly prohibit discrimination or harassment of any kind. We consider all qualified candidates without regard to race, color, religion, age, sex, national origin, disability, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable federal, state, or local laws.