IntelFinance Data Scientist
AI in this role
Job Description:
The Role and Impact
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.
Business group
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.
Key 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.
Qualifications:
Minimum Qualifications
- 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.
Preferred Qualifications
- 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.
We are looking for talented individuals who are ready to take the next step in their career, develop their skills, and contribute to cutting-edge solutions in finance and analytics. Apply today to be part of a dynamic team that is shaping the future of decision-making at Intel.
Job Type:
College GradShift:
Shift 1 (United States of America)Primary Location:
US, Arizona, PhoenixAdditional Locations:
US, California, Santa Clara, US, Oregon, HillsboroPosting Statement:
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of Trust
N/ABenefits
We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.
Annual Salary Range for jobs which could be performed in the US: $98,390.00-163,780.00 USD
The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.*
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.How we rate this
Finance Data Scientist at Intel rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: RAG and AI Agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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