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Data Analyst Jobs in Rochester Hills, MI (NOW HIRING)

Aptiv

QLIK Programmer / Quality Data Analyst

Troy, MI · On-site

QLIK Programmer / Quality Data Analyst Why join Aptiv? You'll have the opportunity to work on cutting-edge applications, develop breakthrough technologies, and deliver innovative solutions to some of ...

USM

Data Analyst-----Need GC and USC

Southfield, MI

Data Analyst Southfield, MI 6+ Months Need GC and USC we're looking for candidates with 3-5+ years of experience. Top 3 skills: Experience writing complex SQL queries Data warehousing concepts Health ...

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All JobsData Analyst JobsData Analyst Jobs in Rochester Hills, MI

Data Analyst information

See Rochester Hills, MI salary details

$31.3K

$76.1K

$125.2K

How much do data analyst jobs pay per year?

As of Aug 17, 2026, the average yearly pay for data analyst in Rochester Hills, MI is $76,066.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,500.00 and $89,300.00 per year, depending on experience, location, and employer.

What is the difference between Data Analyst vs Data Scientist?

AspectData AnalystData Scientist
Required CredentialsBachelor's degree in statistics, mathematics, or related field; often certifications in data analysis toolsBachelor's or master's in computer science, statistics, or related; often advanced certifications or degrees
Work EnvironmentBusiness settings, focusing on data reporting and visualizationResearch and development environments, focusing on predictive modeling and complex algorithms
Employer & Industry UsageRetail, finance, healthcare, and marketing companiesTech firms, research institutions, and large enterprises

While both roles analyze data, Data Analysts primarily focus on interpreting existing data to generate reports and insights, whereas Data Scientists develop predictive models and advanced algorithms to forecast trends and solve complex problems.

Can I learn a data analyst in 3 months?

A data analyst role requires skills in data manipulation, statistics, and tools like Excel, SQL, and Python or R. While three months can provide a foundational understanding through intensive training or bootcamps, gaining proficiency typically takes longer with consistent practice and real-world experience.

What are some common challenges data analysts face when working with large datasets, and how are they typically addressed?

Data Analysts often encounter challenges such as data quality issues, missing or inconsistent values, and slow processing times when handling large datasets. These challenges are typically addressed by implementing data cleaning routines, using advanced data management tools, and leveraging programming languages like Python or R for efficient data manipulation. Collaboration with database administrators and IT teams is also common to ensure data integrity and optimize data storage solutions. Staying updated with best practices in data wrangling and visualization helps Data Analysts deliver accurate and actionable insights.

What work does a data analyst do?

A data analyst collects, processes, and analyzes large datasets to identify trends, patterns, and insights that support business decision-making. They use tools like Excel, SQL, and data visualization software to interpret data and communicate findings to stakeholders. Strong analytical skills and attention to detail are essential for this role.

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and experience with visualization platforms such as Tableau or Power BI are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts interpret data insights and present findings clearly to stakeholders. These skills are crucial for transforming raw data into actionable business insights that drive informed decision-making.

What are top 3 skills for a data analyst?

The top three skills for a data analyst are proficiency in data manipulation and analysis tools like Excel, SQL, and statistical software; strong analytical and problem-solving abilities; and effective communication skills to present insights clearly. Familiarity with data visualization tools such as Tableau or Power BI is also highly valuable. These skills enable data analysts to interpret complex data and support decision-making processes.

What does a data analyst do?

A Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions. They use statistical tools and software to interpret data sets, identify trends, and create visual reports. Data Analysts often collaborate with other departments to provide actionable insights and support strategic planning. Their work helps organizations optimize operations, track performance, and solve business problems using data-driven approaches.
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The top searched job categories for Data Analyst jobs in Rochester Hills, MI are:

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Cities near Rochester Hills, MI with the most Data Analyst job openings:

Data Analyst jobs near you
Infographic showing various Data Analyst job openings in Rochester Hills, MI as of August 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 100% In-person job distribution, with an average salary of $76,066 per year, or $36.6 per hour.

ICT Data & AI Business Analyst

Stellantis

Auburn Hills, MI

Full-time

Re-posted 15 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 44 rated automakers

Job description

Role Summary 

The Data & AI Business Analyst drives the discovery, analysis, and translation of business needs into actionable requirements, with a strong emphasis on data analytics, process optimization, and cross‑functional collaboration. This role requirement‑gathering efforts, shapes analytical solutions, and ensures that data‑driven insights inform strategic and operational decisions. The position serves as a bridge between business stakeholders, data teams, and technology partners to deliver high‑quality, scalable solutions. 

Key Responsibilities 

 Requirements Gathering & Solution Definition 

  • Lead end‑to‑end requirements elicitation through workshops, interviews, process mapping, and data exploration. 
  • Translate business needs into clear, concise functional and non‑functional requirements, user stories, acceptance criteria, and process flows. 
  • Facilitate alignment sessions with stakeholders to validate requirements and ensure shared understanding. 
  • Evaluate business processes and identify opportunities for automation, optimization, and improved data utilization. 

 

Data Analytics & Insights 

  • Partner with data engineering, BI, and analytics teams to define data requirements, metrics, KPIs, and reporting structures. 
  • Analyze complex datasets to identify trends, gaps, and opportunities that inform business strategy. 
  • Support the design and validation of dashboards, analytical models, and data pipelines. 
  • Ensure data quality, governance, and consistency across analytical solutions. 

Stakeholder Communication 

  • Liaison between business units, technical teams, and leadership. 
  • Present findings, recommendations, and solution options to stakeholders in a clear, data‑driven manner. 
  • Manage stakeholder expectations, dependencies, and priorities across multiple initiatives. 
  • Mentor junior analysts and contribute to BA practice development. 

Project & Delivery Support 

  • Collaborate with project managers, product owners, and technical leads to define scope, timelines, and delivery plans. 
  • Support backlog refinement, sprint planning, and release readiness activities. 
  • Conduct impact assessments, risk analysis, and change‑readiness evaluations. 
  • Validate solutions through testing support, UAT coordination, and post‑implementation reviews. 

Required Qualifications 

  • Bachelor's degree in Business, Computer Science, Information Systems, Data Analytics, Statistics, or a related field
  • Minimum 4 years of experience as a Business Analyst, Data Analyst, or similar role 
  • Strong proficiency in data analysis tools (e.g., SQL, Excel, Power BI, Tableau). 

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