Data Scientist / ML Engineer at Franklin Templeton designing and productionizing machine learning systems for business solutions. Collaborating with teams to deliver scalable and reliable ML solutions.
About the role
- Data Scientist at GE Vernova focusing on operationalizing Generative AI strategy with complex business data. Leading exploratory analysis and data management to inform AI models and business objectives.
Responsibilities
- be part of a data science or cross-disciplinary team developing innovative solutions, typically involving large, complex data sets to achieve business outcomes
- lead extended team members from the Emerging Technology Guild and functional DT teams to develop and operationalize data science solutions are ready for scale-up
- perform comprehensive exploratory data analysis (EDA) on diverse and complex business datasets, using statistical analysis, Natural Language Processing (NLP), and unsupervised clustering techniques to uncover patterns, identify quality issues, and extract meaningful insights
- collaborate closely with business Subject Matter Experts (SMEs) to translate their deep domain knowledge into structured, AI-ready datasets for use in prompt engineering, Retrieval-Augmented Generation (RAG), and model fine-tuning
- develop and prepare "golden datasets" that serve as pristine examples of our business processes, significantly reducing the iteration time for prompt engineering and AI development teams
- design, create, and maintain a suite of data benchmarks that represent our core business use cases
Requirements
- Bachelor’s or Master’s degree in a quantitative field such as Data Science, Computer Science, Statistics, Economics, or a related discipline
- 3-5+ years of professional experience as a Data Scientist, Data Analyst, or in a similar role with a heavy emphasis on data exploration, manipulation, and preparation
- Strong proficiency in Python and core data science libraries (e.g., pandas, NumPy, scikit-learn, spaCy, NLTK)
- Demonstrated experience with a wide range of exploratory data analysis and unsupervised machine learning techniques (e.g., clustering, topic modeling, dimensionality reduction)
- Proven ability to work with messy, unstructured, and semi-structured data, especially text.
- Exceptional communication and interpersonal skills, with a talent for translating complex technical concepts to non-technical audiences and building strong relationships with business stakeholders.
Benefits
- medical, dental, vision, and prescription drug coverage
- access to Health Coach from GE Vernova, a 24/7 nurse-based resource
- access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
- GE Vernova Retirement Savings Plan
- tax-advantaged 401(k) savings opportunity with company matching contributions
- company retirement contributions
- access to Fidelity resources and financial planning consultants
- tuition assistance
- adoption assistance
- paid parental leave
- disability benefits
- life insurance
- 12 paid holidays
- permissive time off
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