Data Scientist – GenAI & ML

TechDigital
  • Princeton, NJ
    12 days ago

    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"

    Numbers & Facts

    LocationPrinceton, NJ
    IndustryOther/Not Classified
    Company Size100 to 499 employees

    Skills

    • Algorithmsunmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Best Practicesunmatched
    • Business Analysisunmatched
    • Business Solutionsunmatched
    • Communication Skillsunmatched
    • Computer Programmingunmatched
    • Computer Scienceunmatched
    • Computer Skillsunmatched
    • Conferencesunmatched
    • Cross-Functionalunmatched
    • Data Analysisunmatched
    • Data Miningunmatched
    • Data Processingunmatched
    • Data Qualityunmatched
    • Data Scienceunmatched
    • Data Visualizationunmatched
    • Database Extract Transform and Load (ETL)unmatched
    • Detail Orientedunmatched
    • Distributed Computingunmatched
    • Documentation Modelsunmatched
    • Experiment Designunmatched
    • Financial Servicesunmatched
    • Gitunmatched
    • GitHubunmatched
    • Industry/Trade Analysisunmatched
    • Insuranceunmatched
    • Insurance Underwritingunmatched
    • Leadershipunmatched
    • Machine Learningunmatched
    • Mathematicsunmatched
    • Mentoringunmatched
    • Model Reviewunmatched
    • Model Validationunmatched
    • Natural Language Processing (NLP)unmatched
    • Neural Networksunmatched
    • Performance Analysisunmatched
    • Predictive Modelingunmatched
    • Problem Solving Skillsunmatched
    • Product Engineeringunmatched
    • Project Designunmatched
    • Project Estimatesunmatched
    • Project/Program Managementunmatched
    • Prototypingunmatched
    • Python Programming/Scripting Languageunmatched
    • Quality Controlunmatched
    • Regular Expressionsunmatched
    • SQL (Structured Query Language)unmatched
    • Sample Designunmatched
    • Software Engineeringunmatched
    • Source Code/Configuration Management (SCM)unmatched
    • Statistical Modelingunmatched
    • Statisticsunmatched
    • Technical Leadershipunmatched
    • Testingunmatched
    • Training Data Setsunmatched
    • Usability Engineeringunmatched
    • Use Casesunmatched
    • User Interface/Experience (UI/UX)unmatched

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