Cons - TC - AI and Quant Modelling - AI Data Scientist - Manager - Multiple Positions - 1705472

EY•San Francisco, CA

1d•Hybrid

About The Position

This role involves working with a wide variety of clients to deliver the latest data science, big data technologies, and operations research techniques and practices to design, build and maintain scalable and robust solutions that unify, enrich and analyze data from multiple sources. The position requires creating well-rounded approaches to help clients navigate the complex world of modern data science, analytics, and software engineering. It also involves providing clients with a unique business perspective on how data science and analytics can transform and improve their entire organization, clarifying problems by driving to understand the true issue. The role leverages Machine Learning (ML) workflows including ingesting, analyzing, and transforming data and evaluating results to make meaningful predictions and solve problems by incorporating data into decision making. It also involves applying data mining and statistical analysis techniques like hypothesis testing, segmentation and modelling to analyze large amounts of data. The role utilizes generative AI modelling and frameworks and large language models (LLMs) to help clients make data-driven decisions by working with structured and unstructured data sets, building out predictive models and advising clients on data mining leading practices. Additionally, it involves building and applying data analysis algorithms including data mining, statistics, machine learning, natural language processing, sentiment analysis, and text mining. The role requires designing, architecting and developing solutions leveraging data technologies to ingest, process and analyze large, disparate data sets to exceed business requirements. It also includes designing, building, and maintaining ML models, frameworks, and pipelines as well as designing and deploying end-to-end ML workflows in order to unify, enrich and analyze customer data to derive new insights and opportunities. The position also entails managing and motivating teams of professionals with diverse skills and backgrounds, consistently delivering quality client services by monitoring progress, demonstrating in-depth technical capabilities and professional knowledge, maintaining long-term client relationships and networks, and cultivating business development opportunities.

Requirements

Bachelor's degree in Mathematics, Information Systems, Statistics, Operations Research, Data Science, Analytics, Computer Science, Engineering, Machine Learning, or a related field and 5 years of progressive, post-baccalaureate related work experience. Alternatively, must have a Master's degree in Mathematics, Information Systems, Statistics, Operations Research, Data Science, Analytics, Computer Science, Engineering, Machine Learning, or a related field and 4 years of related work experience.
3 years of experience in any combination of external advisory professional services, external consulting, or customer success.
4 years hands-on working experience with artificial intelligence, machine learning, data science, or data engineering.
4 years of experience working with Python.
2 years of combined experience using any combination of at least 2 of the following Generative AI models and frameworks: OpenAI family, Open source LLMs, Dall-e, LlamaIndex, Langchain, Retrieval Augmented Generation (RAG), Other frontier model families (e.g. Anthropic).
1 year of combined experience using DevOps tools GIT and Azure DevOps as well as Agile tools to develop and deploy analytical solutions with multiple features, pipelines, and releases.
2 years of experience designing, building, and maintaining ML models, frameworks, and pipelines as well as designing and deploying end to end ML workflows on at least one major cloud computing platform.
4 years of experience with data manipulation tools and libraries SQL, Pandas, or Spark.
2 years of experience with containerization and scaling models as well as integrating models and feedback from downstream consumption systems.
2 years of experience directly managing technical teams.
Requires travel up to 80%, of which 10% may be international, to serve client needs.
Employer will accept any suitable combination of education, training, or experience.

Responsibilities

Design, build and maintain scalable and robust solutions that unify, enrich and analyze data from multiple sources.
Leverage Machine Learning (ML) workflows including ingesting, analyzing, and transforming data and evaluating results to make meaningful predictions and solve problems by incorporating data into decision making.
Apply data mining and statistical analysis techniques like hypothesis testing, segmentation and modelling to analyze large amounts of data.
Use generative AI modelling and frameworks and large language models (LLMs) to help clients make data-driven decisions by working with structured and unstructured data sets, building out predictive models and advising our clients on data mining leading practices.
Build and apply data analysis algorithms including data mining, statistics, machine learning, natural language processing, sentiment analysis, and text mining.
Design, architect and develop solutions leveraging data technologies to ingest, process and analyze large, disparate data sets to exceed business requirements.
Design, build, and maintain ML models, frameworks, and pipelines as well as design and deploy end to end ML workflows in order to unify, enrich and analyze customer data to derive new insights and opportunities.
Manage and motivate teams of professionals with diverse skills and backgrounds.
Consistently deliver quality client services by monitoring progress.
Demonstrate in-depth technical capabilities and professional knowledge.
Maintain long-term client relationships and networks.
Cultivate business development opportunities.