Data Scientist - GenAI & ML
Omni Inclusive14 days ago
Princeton, NJ, United States
Hybrid
Full-time
Junior Level (1-3 years)
Job Description
Must have:
- Python Programming
- Pytorch
- NLP
- ML modeling/development
- GenAI
- SQL
- LLMs, RAG architecture, and agentAI frameworks
Key Responsibilities:
- Lead use case/workstream with junior data scientists
- Contribute to the end-to-end model lifecycle, including data exploration and understanding, feature engineering, model training and validation, ensuring quality, security, scalability, and fairness
- Support use case development that includes initial project scoping, project/sample design, reception and processing of data, performing analysis and modeling to creation of final report/presentation
- Data wrangling/data matching/ETL to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets
- Utilizing advanced statistical and AI/ML techniques to create high-performing predictive models and creative analyses to address business objectives and partner needs
- Identification of source data and data quality checks both in model/solution development and in production
- Packaging of model/solution and deployment in cooperation with Data Engineers and MLOps
- Implement new statistical or other mathematical methodologies as needed for specific models or analysis.
- Propose innovative ways to look at problems through using data mining and data visualization
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Present information using data visualization techniques; communicate results and ideas to key decision makers.
- Ensure data accuracy and consistent reporting by performing regular data quality control, prepare and maintain reports, and troubleshoot data anomalies
- Adhere to model governance, documentation, testing, and other best practices in partnership with key stakeholders.
- Consistent accuracy and thoroughness in performing work assignments
- Attend industry conferences to stay current on industry trends, challenges, and potential market opportunities
- Contribute to standardization of Data Science tools, processes, and best practices
- Build LLM/AI powered application prototypes with lightweight UI (e.g., Streamlit) to validate usability and support adoption.
Required Skills:
- PhD with 2+ years of experience, Master's degree with 4+ years of experience in Statistics, Computer Science, Engineering, Applied mathematics or related field
- 3+ years of hands-on ML modeling/development experience
- Background in insurance and underwriting preferred
- Solid understanding of data analysis and statistical modeling.
- Knowledge of a variety of machine learning techniques (clustering, decision tree, bagging/boosting artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Demonstrated track records in experimental design and executions
- Hands-on experience with data wrangling including fuzzy matching and regular expression, distributed computing and applying parallelism to ML solutions
- Strong programming skills in Python
- Solid background in algorithms and a range of ML models
- Excellent communication skills and ability to work and collaborate cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level
- Excellent analytical and problem-solving abilities with superb attention to detail
- Proven experience in providing technical leadership and mentoring to data scientists and strong project management skills with ability to monitor/track performance for enterprise success
- Experience communicating complex ideas simply, presenting impact, trade-offs, and recommendations to non-technical partners.
- Working knowledge of core software engineering concepts (version control with Git/GitHub, testing, logging, ...).
- Working knowledge of NLP, LLMs, RAG architecture, and agent frameworks, including safe automation design and evaluation systems.
- Experience in insurance, financial services, or related industries is a plus
Required Skills
RAG architecture
NLP
agentAI frameworks
Experimental design
Data visualization
GenAI
ML modeling/development
SQL
Python Programming
Algorithms
Pytorch
LLMs
ETL
Machine learning techniques
Statistical modeling
Data wrangling