ZipRecruiter

Log In

1

Business Intelligence Data Scientist Jobs (NOW HIRING)

COCC

Business Intelligence Data Analyst

Camp Hill, PA · Hybrid

$80K - $109K/yr

Our client is seeking a Business Intelligence Data Analyst to support reporting, analytics, and ... Bachelor's degree in Data Analytics, Information Systems, Computer Science, Statistics, or a ...

next page

Showing results 1-20

All JobsBusiness Intelligence Data Scientist Jobs

Business Intelligence Data Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do business intelligence data scientist jobs pay per year?

As of Sep 3, 2026, the average yearly pay for business intelligence data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a business intelligence data scientist?

A Business Intelligence (BI) Data Scientist is a professional who analyzes complex data sets to help organizations make informed business decisions. They combine expertise in data analytics, statistics, and business knowledge to uncover trends, patterns, and insights from large volumes of data. BI Data Scientists use tools like SQL, Python, and visualization software to present actionable recommendations to stakeholders. Their work supports strategic planning, improves operational efficiency, and drives business growth.

How does a business intelligence data scientist typically collaborate with other departments within an organization?

Business Intelligence Data Scientists frequently work cross-functionally with teams such as IT, marketing, sales, and finance to identify data needs and translate business questions into analytical projects. They collaborate closely with business analysts to understand requirements and with data engineers to ensure data pipelines are accurate and efficient. Effective communication is key, as they must present complex findings in a clear way to stakeholders who may not have technical backgrounds. This collaborative environment helps drive data-driven decision making across the organization.

What are the key skills and qualifications needed to thrive as a business intelligence data scientist, and why are they important?

To thrive as a Business Intelligence Data Scientist, you need expertise in statistical analysis, data modeling, and a strong background in mathematics or computer science, often supported by a relevant degree. Proficiency in tools like SQL, Python, R, data visualization platforms (e.g., Tableau, Power BI), and experience with big data systems are commonly required. Strong problem-solving, communication, and business acumen help translate complex data insights into actionable strategies for stakeholders. These skills enable effective data-driven decision-making, maximizing business value and competitive advantage.

What is the difference between Business Intelligence Data Scientist vs Business Intelligence Analyst?

AspectBusiness Intelligence Data ScientistBusiness Intelligence Analyst
CredentialsOften requires a degree in data science, statistics, or related fields; certifications like Certified Analytics ProfessionalTypically holds a degree in business, IT, or related fields; certifications like Microsoft Certified Data Analyst
Work EnvironmentFocuses on advanced data modeling, predictive analytics, and machine learning in data-driven teamsConcentrates on reporting, dashboards, and data visualization for business decision-making
Industry UsageUsed across industries for complex data analysis and predictive modelingCommonly employed in business settings for reporting and performance tracking

The main difference is that Business Intelligence Data Scientists focus on advanced analytics, predictive modeling, and data science techniques, while Business Intelligence Analysts primarily handle reporting, data visualization, and supporting business decisions with existing data. Both roles are essential in data-driven organizations but serve different analytical needs.

Is business intelligence still in demand?

Business Intelligence Data Scientists are in high demand as organizations increasingly rely on data analysis, visualization, and tools like SQL, Tableau, and Power BI to make strategic decisions. The role continues to grow with the expansion of big data and analytics, requiring skills in data modeling, statistical analysis, and programming languages such as Python or R.

What is data science in business intelligence?

Data science in business intelligence involves analyzing large datasets to extract insights that support strategic decision-making. Business intelligence professionals use tools like SQL, Python, or Tableau to visualize data trends and patterns, enabling organizations to improve operations and identify opportunities. Strong analytical skills and knowledge of data modeling are essential in this role.
More about Business Intelligence Data Scientist jobs

What cities are hiring for Business Intelligence Data Scientist jobs?

Cities with the most Business Intelligence Data Scientist job openings:

What job categories do people searching Business Intelligence Data Scientist jobs look for?

The top searched job categories for Business Intelligence Data Scientist jobs are:

Business Intelligence Data Scientist jobs near you
Infographic showing various Business Intelligence Data Scientist job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Hybrid job distribution, with an average salary of $122,738 per year, or $59 per hour.

Business Intelligence Data Scientist

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 10 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

13th of 45 rated automakers

Job description

Stellantis is seeking a highly skilled Business Intelligence Data Scientist to support advanced analytics within the Business Intelligence and Data Analytics team at the Headquarters & Technology Center in Auburn Hills, Michigan. This role is responsible for applying advanced analytical techniques to large and complex datasets in order to generate actionable insights that inform business decisions related to warranty, cost, quality performance, and operational effectiveness.
The Data Scientist will work with a variety of internal data sources to develop analytical solutions, perform deep exploratory analysis, and support predictive, diagnostic, and prescriptive analytics efforts. The role requires strong analytical thinking, statistical expertise, and the ability to clearly communicate findings to both technical and non-technical stakeholders.
The successful candidate will collaborate closely with Engineering, Quality, Finance, and IT partners and operate with a high degree of independence in a fast-paced, data-driven environment.
Key Responsibilities:
  • Analyze large, complex datasets to identify trends, relationships, risks, and opportunities related to warranty and quality performance
  • Develop and apply advanced statistical, analytical, and data science techniques to support business problem-solving and decision-making
  • Perform exploratory data analysis and root-cause investigations to explain performance drivers and anomalies
  • Design, develop, and maintain robust analytical models, metrics, and methodologies
  • Translate complex analytical results into clear insights, recommendations, and visualizations for stakeholders
  • Partner with cross-functional teams to understand business needs and deliver analytical solutions
  • Ensure analytical outputs are accurate, repeatable, and well-documented
  • Support continuous improvement of analytics processes, tools, and data usage practices
  • Contribute to the development of standardized reporting, metrics, and best practices across the organization

Basic Qualifications:
  • Bachelor's degree in a quantitative discipline such as Data Science, Statistics, Computer Science, Applied Mathematics, or a related field
  • Relevant internship experience
  • Demonstrated ability to communicate analytical findings clearly to technical and non-technical audiences
  • Excellent problem-solving, organizational, and time-management skills
  • Ability to work independently with minimal supervision

Preferred Qualifications:
  • Master's degree in a quantitative discipline
  • Experience applying predictive, diagnostic, or prescriptive analytics techniques in a business environment
  • Familiarity with data visualization and business intelligence tools (e.g., Power BI, Tableau)
  • Experience working in automotive, manufacturing, quality, or operational analytics environments
  • Experience with working across multiple deployment environments including cloud, on-premises and hybrid, using multiple operating systems
  • Experience translating complex data into clear narratives for leadership decision-making

What Stellantis employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply