Finance Data Scientist

Intel Corporation•Santa Clara, CA

1d•$98,390 - $163,780•Hybrid

About The Position

As a Data Scientist, you will leverage your expertise in data analysis, predictive modeling, and coding to uncover actionable insights from structured and unstructured data. This role is integral to solving business problems, driving better decision-making, and enabling innovative solutions. You will design scalable data-driven applications, create visualizations, and communicate findings to diverse stakeholders, contributing directly to the organization's success. The role will focus on building AI-powered applications and agents for Finance. The Finance Data and AI organization operates within Intel's Finance group, focusing on harnessing advanced analytics and artificial intelligence to drive financial decision-making and optimize business performance. This team plays a critical role in supporting Intel's broader goals by delivering data-driven insights and solutions that enhance operational efficiency and strategic planning.

Requirements

Bachelor's degree in a relevant field with 0-1 years of hands-on experience in the domain with demonstrated skills gained through internships, academic projects, coursework, or hands-on training OR a Master's degree in a relevant field with no prior professional experience.
Proficiency in Python and SQL.
Knowledge of predictive modeling, machine learning algorithms, and statistical analysis techniques.
Understanding of big data frameworks and principles.
Hands-on experience building an application using a large language model (LLM), including integration through code with an API or model library, demonstrated through coursework, internships, or personal projects.

Nice To Haves

Strong communication skills to explain complex findings in a clear and impactful manner.
Ability to work collaboratively in cross-functional teams.
Enthusiasm for learning and applying innovative data science methodologies.
Familiarity with retrieval-augmented generation (RAG), agent tool calling, or reusable AI components that accelerate application development.
Familiarity with data visualization tools like Tableau or Power BI.

Responsibilities

Develop algorithms, predictive models, and applications to solve complex business problems using data science techniques.
Perform large-scale experimentation, statistical analysis, and interpret structured and unstructured datasets to derive meaningful insights.
Design and implement visualizations, dashboards, and presentations to effectively communicate data-driven findings.
Detect and correct data anomalies, ensuring high-quality datasets for analysis.
Develop and test LLM-powered applications and AI agents that connect to approved data sources and tools to support financial analysis and automate workflow steps, with appropriate validation and human review.
Collaborate with cross-functional teams to explore, compile, and analyze diverse big data sources, ensuring models are scalable and implementable. Partner with Finance experts to understand data, metric definitions, and business processes.
Drive the adoption of standard methodologies for coding, analytics, modeling, and experimentation within data science projects.
Troubleshoot service offerings using proprietary analytical platforms, commercial tools, and custom scripts.