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Business Intelligence Data Scientist Jobs (NOW HIRING)

Business Intelligence Data Analyst

Seattle, WA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

In order to continue and accelerate our growth, we are looking for a Business Intelligence Data Analyst to add to our Seattle, Washington-based team. The BI Data Analyst will review functional ...

Business Intelligence Data Engineer

$52.25 - $67.75/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking a highly skilled Business Intelligence Engineer to design, build, and optimize our Power BI environment and data infrastructure. This role combines technical expertise with team ...

... Business Intelligence, Data Management, SOA, BPM, Data Warehousing, SharePoint Consulting and ... Data Scientist Location: San Ramon, CA Start Date: Immediate Duration: 3-6 months MUST BE LOCAL ...

Showing results 21-40

Business Intelligence Data Scientist information

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$37.5K

$122.7K

$196.5K

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

As of Aug 14, 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.

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, Python, and Tableau to make strategic decisions. The role continues to grow with the expansion of big data and analytics across industries, requiring strong technical skills and domain knowledge.

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.

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.

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 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.

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:

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.

Data Intelligence - Data Scientist

Ampcus Inc

Washington, DC • On-site

Full-time

Re-posted 5 days ago


Job description

Job Summary:
Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. They are seeking a highly motivated Data Scientist to develop algorithms, build predictive analytics, and apply machine learning to improve claim processing and provider prediction for FEP Client plans. The role involves working with the development team to enhance machine learning services and deliver better products through data-driven decision making.
Responsibilities:
• Develop algorithms, write scripts, build predictive analytics, use automation, apply machine learning, and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help senior leadership make informed decisions.
• Provide the team with a deep understanding of their data, what it all means, and how they can use it.
• Help with discovering the information hidden in vast amounts of data, and help with making smarter decisions to deliver even better products.
• Applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with products.
• Development new ML model(s) as well as maintaining existing ones and their processes.
• Development Gen AI solution using AI platform like AWS SageMaker, AWS Bedrock, AWS AgentCore.
• Select features, building and optimizing classifiers using machine learning techniques, data mining using state-of-the-art methods, and, enhancing data collection procedures to include information that is relevant for building analytic systems.
• Responsibilities will also include processing, cleansing, and verifying the integrity of data used for analysis and doing ad-hoc analysis and presenting results in a clear manner.
• Creating automated anomaly detection systems and constant tracking of its performance.
Qualifications:
Required:
• Master's Degree or Ph.D. in STEM with 2 years preferred OR Bachelor’s Degree in STEM with 7 years.
• Experience in predictive modeling, data science, machine learning, or user and entity behavior analytic development.
• Experience in developing predictive, prescriptive, optimization, and forecasting models, including the use of contemporary techniques such as and not limited to support vector machines, neural networks, and gradient boosting.
• Experience in developing of Generative AI solution with LLM and custom model to provide AI solution to business.
• Experience in interpreting results from statistical and mathematical models.
• A minimum of two years’ experience in applying Data Science/ Analytics to Health Insurance/Health Care related problems/use cases.
• At least 1 years focused on applications of Generative AI solution.
• Experience in programming languages like Java, Python and/or R for complex data manipulation, statistical analysis, and machine learning.
• Experience in Analytic development with streaming and a Hadoop ecosystem (Hive, Spark, etc.)
• Experience in SQL, NoSQL, graph-based, Key/Value stores, document stores.
• Experience with cloud base data platform like Snowflake and use training/build model.
• Experience with one or more cloud services (AWS SageMaker, MS Azure)
• Experience applying machine learning to real-world production systems, analytic development based on SparkML and other ML libraries.
• Experience in advanced data visualizations and interpretation using data visualization tools is plus (e.g., Tableau, Power BI).
• Familiarity with common Linux/Unix command line tasks and version control software like git or svn preferable.
• Using and developing statistical analysis, modeling, simulation, and machine learning methods.
• Comfort with complex mathematical concepts and models.
• Experience with Agile Methodology/Scrum Development and DevOps
• History of solving difficult problems using a scientific approach highly preferred
• Ability to communicate and present the work effectively and influence others
• Ability to work in a fast paced environment and shift gears quickly
Company:
Ampcus is a global business, technology consulting and an staff augmentation firm specializing in AI/ML,digital solutions, Cybersecurity & Risk management, Testing, Forensics & Fraud services and human capital management. Founded in 2004, the company is headquartered in Chantilly, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

Ampcus logo

About Ampcus

Sourced by ZipRecruiter

Ampcus Inc. is a ISO 20000, ISO 27000, ISO 9001, CMMI DEV/3 SM and CMMI SVC/3 SM certified global provider of a broad range of Technology and Business consulting services. From strategy to execution, our disciplined yet flexible approach starts and ends with our clients. By listening hard and working harder, client goals become our goals. Their success is our satisfaction. It’s why our clients sleep well at night. We believe that the success of an engagement is determined by strong project management, as well as clear communication and mutual commitment working collaboratively. Our methodology begins with listening to the customer about their needs, then working with their team to gain a clear understanding of the requirements, while providing knowledge transfer of best practices for the organization.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chantilly, VA, US

Year founded

2004