Service Delivery Center, AI & Data, Data Scientist - Senior - Jacksonville

At EY, we’re all in to shape your future with confidence. 

 

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.  Join EY and help to build a better working world.

 

Senior Data Scientist

 

EY is the only professional services firm with a separate business unit (“FSO”) that is dedicated to the financial services marketplace. Our FSO teams have been at the forefront of every event that has reshaped and redefined the financial services industry. This practice also has several Service Delivery Centers that are made up of high-performing US-based resources who work closely with our experienced client-serving professionals to deliver project-based work and managed services to our US-based Financial Services clients. If you have a passion for rallying together to solve the most complex challenges in the financial services industry, come join our dynamic FSO team!

 

The opportunity

Data has yet to be utilized to its fullest potential. Financial institutions are looking to build smarter and more efficient ways to operate their business, through new opportunities uncovered by their data. You’ll be solving complex problems, as well as giving deliverables to our clients in the AI and data space. With support from a highly talented team, you’ll have tremendous growth opportunities, with a focus on continuous learning and skills development to become a leader that can make significant contributions to companies.

 

Key Responsibilities

• Strategic Data Analysis & Insight Generation: Lead complex data analysis to uncover strategic insights, identify implications, and provide data-driven recommendations, effectively communicating findings through clear data visualizations.
• Advanced AI/ML Model Development: Design, develop, and implement advanced machine learning models and statistical analyses to solve complex business challenges, leveraging diverse banking data.
• Generative AI & NLP: Drive Generative AI initiatives by developing and fine-tuning LLMs, applying efficient prompting strategies, utilizing LLMs for data augmentation, and integrating Retrieval-Augmented Generation (RAG, including advanced RAG) to enhance capabilities. Design and deploy high-accuracy NLP models for diverse applications.
• Deep Learning Implementation: Apply advanced deep learning techniques (ANN, LSTM, CNN, BERT, XLNet, Transformers, neural & LLM-based embeddings) to create state-of-the-art AI models and applications.
• Research & Innovation: Proactively research and develop innovative AI solutions, staying abreast of the latest advancements in AI/ML to drive continuous business improvement.
• Technical Expertise & Development: Demonstrate deep proficiency in Python (scikit-learn, pandas, SpaCy, TensorFlow, PyTorch, transformers) and PySpark (including MLLib, SparkNLP). Utilize big data frameworks (Hive, Hue; with exposure to Impala, Spark streaming) to drive end-to-end modelling efforts.
• Business Translation & Communication: Translate intricate business requirements into technical solutions, ensuring strong alignment and clear communication with stakeholders. Influence and collaborate effectively with cross-functional teams.
• Risk Management & Compliance: Actively assess and mitigate risks associated with data-driven decisions, upholding firm reputation, safeguarding assets, and ensuring strict compliance with regulations, policies, and ethical standards.

 

Qualifications

 

• Experience: 8+ years in ML/AI development, or 4+ years with a PhD in a related field. At least 2 years of direct experience in Generative AI/LLM development.

 

• Technical Skills:
• Hands-on expertise in statistical analysis and machine learning modelling.
• Proficiency in Python and essential packages (scikit-learn, pandas, SpaCy, TensorFlow, PyTorch, transformers).
• Proficiency in PySpark and big data frameworks (Hadoop, Spark, Hive, Hue).
• Expertise in NLP and deep learning frameworks.
• Proven experience with generative AI development, including prompting, RAG, and LLM fine-tuning using packages like Langchain, LlamaIndex.
• Strong knowledge of data modelling techniques.
• Good to have: Exposure to graph neural networks and graph databases.
• Analytical & Problem-Solving: Exceptional ability to use complex analytical, interpretive, and problem-solving techniques; demonstrated