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Compensation Data Analytics Jobs in Michigan (NOW HIRING)

Canopy

Senior Data Analyst

Detroit, MI · On-site +1

$96K - $132K/yr

As a Senior Data Analyst reporting to the Team Manager of Core AI and Data, you will spearhead the ... Life insurance and accidental death & dismemberment insurance Compensation Range Compensation may ...

Wayne State University

Compensation Professional

Detroit, MI · On-site

$82K - $106K/yr

ESSENTIAL FUNCTIONS Conducts job analysis and evaluations. Prepares s. Completes compensation surveys. Identifies, evaluates and communicates qualitative and quantitative data trends to assist ...

Pwc

AI & GenAI Data Scientist-Director

Grand Rapids, MI · On-site

$155K - $410K/yr

Within our Data and Analytics Engineering practice, you will apply data, algorithms, and software ... Actual compensation within the range will be dependent upon the individual's skills, experience ...

Pwc

AI & GenAI Data Scientist-Director

Detroit, MI

$155K - $410K/yr

Within our Data and Analytics Engineering practice, you will apply data, algorithms, and software ... Actual compensation within the range will be dependent upon the individual's skills, experience ...

Reply

Manager, Data Engineering

Detroit, MI

$160K - $190K/yr

Contributing to and overseeing the successful delivery of data platform, analytics, and data ... The base compensation range for this full-time position is between $160,000 - $190,000 plus ...

Reply

Manager, Data Engineering

Detroit, MI · On-site

$160K - $190K/yr

Contributing to and overseeing the successful delivery of data platform, analytics, and data ... The base compensation range for this full-time position is between $160,000 - $190,000 plus ...

Reply

Manager, Data Engineering

Detroit, MI · On-site

$160K - $190K/yr

Contributing to and overseeing the successful delivery of data platform, analytics, and data ... The base compensation range for this full-time position is between $160,000 - $190,000 plus ...

Corning

$104K - $125K/yr

As a Data Engineer, you will build, maintain, and support data pipelines and cloud-based data ... analytics, and business teams.- Competitive compensation and benefits. More about us Corning is one ...

Pwc

Data Engineer - Senior Associate

Detroit, MI · On-site

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... Actual compensation within the range will be dependent upon the individual's skills, experience ...

Pwc

Data Engineer - Senior Associate

Grand Rapids, MI

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... Actual compensation within the range will be dependent upon the individual's skills, experience ...

Atwell, LLC

Director of Total Compensation & Benefits

Troy, MI · On-site

$118K - $162K/yr

Advanced Excel, reporting, modeling, and data-analysis skills. * Strong attention to detail and discretion when managing confidential compensation and equity information. * Ability to present complex ...

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Compensation Data Analytics information

What is compensation data analytics?

Compensation data analytics is the process of collecting, analyzing, and interpreting data related to employee compensation, such as salaries, bonuses, and benefits. This field helps organizations make informed decisions about pay structures, ensure competitive and equitable compensation, and comply with legal requirements. By leveraging data analytics, companies can identify trends, address pay disparities, and optimize their compensation strategies to attract and retain top talent.

What are the key skills and qualifications needed to thrive as a Compensation Data Analytics professional, and why are they important?

To thrive as a Compensation Data Analytics professional, you need strong analytical skills, a solid understanding of compensation structures, and a degree in fields like HR, finance, or statistics. Familiarity with HR information systems (HRIS), data visualization tools like Tableau or Power BI, and proficiency in Excel or statistical software such as R or Python are commonly required. Attention to detail, problem-solving abilities, and effective communication skills help you translate complex data into actionable insights for stakeholders. These skills ensure accurate, data-driven compensation strategies that support organizational goals and fair employee practices.

What is the difference between Compensation Data Analytics vs Compensation Analyst?

AspectCompensation Data AnalyticsCompensation Analyst
CredentialsDegree in HR, Business, or Data Analytics; often certifications in data analysisDegree in HR, Business, or related field; HR certifications common
Work EnvironmentData-focused, analytical tasks, often in HR or compensation departmentsHR teams, compensation planning, employee benefits
Industry UsageUsed across industries for data-driven compensation strategiesPrimarily in HR and compensation departments within various industries
Search & Comparison IntentFocus on data analysis skills and tools for compensation dataFocus on salary structures, benefits, and employee compensation policies

Compensation Data Analytics involves analyzing large datasets to inform compensation strategies, requiring strong data skills. Compensation Analysts focus on designing and managing salary structures and benefits. Both roles collaborate but differ mainly in their focus—data analysis versus policy implementation.

Is data analytics a high paying job?

Data analytics roles, including Compensation Data Analytics, are generally considered well-paying careers, especially for those with strong skills in statistical analysis, data visualization, and tools like Excel or SQL. Salaries tend to increase with experience, certifications, and advanced skills such as machine learning or programming languages like Python. Overall, data analytics is regarded as a lucrative field within the broader data and technology sectors.

How does a Compensation Data Analytics professional typically collaborate with HR and business leaders to inform pay decisions?

Compensation Data Analytics professionals work closely with HR teams and business leaders by providing data-driven insights that guide salary structures, incentive plans, and pay equity initiatives. They interpret data from salary surveys, internal pay records, and market trends, translating complex analyses into actionable recommendations. Regular meetings and presentations are common, ensuring that stakeholders understand compensation trends and can make informed decisions that support organizational goals. Effective communication and collaboration are key, as these professionals often bridge the gap between technical analytics and strategic HR planning.
What are popular job titles related to Compensation Data Analytics jobs in Michigan? For Compensation Data Analytics jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Compensation Data Analytics jobs in Michigan look for? The top searched job categories for Compensation Data Analytics jobs in Michigan are:
What cities in Michigan are hiring for Compensation Data Analytics jobs? Cities in Michigan with the most Compensation Data Analytics job openings:
Compensation Data Analytics jobs near you

Senior Data Analyst

Canopy

Detroit, MI • On-site, Remote

$96K - $132K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 14 days ago

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Job description

Join Canopy, a Ford-backed company, at the forefront of engineering advanced threat detection and deterrence products specifically designed for vehicles. Our mission is to eliminate vehicle crime and enhance mobility through cutting-edge consumer hardware, aftermarket connectivity, and AI-driven security solutions. As part of our team, you'll be at the forefront of innovation, helping to solve one of today's most pressing challenges with cutting-edge solutions.
As a Senior Data Analyst reporting to the Team Manager of Core AI and Data, you will spearhead the design, development, and implementation of cutting-edge machine learning models and algorithms to address intricate business challenges. Your role will involve analyzing large datasets to identify meaningful patterns, trends, and relationships, using a combination of statistical methods, machine learning techniques, and data visualization tools. Additionally, you will be responsible for developing and validating approaches that ensure accuracy, robustness, and scalability for production deployment.
Responsibilities:
  • Lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex business problems.
  • Collaborate with cross-functional teams, including product managers, engineers, and business stakeholders, to identify data-driven opportunities and translate them into actionable insights.
  • Analyze large datasets to extract meaningful patterns, trends, and relationships, leveraging statistical methods, machine learning techniques, and data visualization tools.
  • Develop and validate approaches, ensuring accuracy, robustness, and scalability for deployment in production environments.
  • Communicate findings and recommendations to both technical and non-technical audiences through detailed reports, presentations, and data visualizations.
  • Mentor and provide guidance to junior data scientists and analysts, fostering a culture of continuous learning and innovation.

Requirements
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  • 5+ years of experience in data science, with a strong background in statistical analysis, machine learning, and predictive modeling.
  • Proficiency in programming languages such as Python.
  • Strong expertise in SQL and experience working with large-scale databases and data processing frameworks.
  • Demonstrated ability to work with complex data sets, including data cleaning, transformation, and feature engineering.
  • Experience with data visualization tools such as Tableau, Grafana, or Matplotlib to present insights and results effectively.
  • Strong problem-solving skills, with the ability to work independently and manage multiple projects simultaneously.
  • Excellent communication skills, both written and verbal, with the ability to convey complex technical concepts to non-technical stakeholders.

Preferred Qualifications:
  • Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related field.
  • Experience with deep learning techniques and frameworks such as TensorFlow, or PyTorch.
  • Familiarity with cloud computing platforms like AWS, Azure, or Google Cloud.
  • Experience where data science has driven significant business outcomes.
  • Strong understanding of A/B testing, experimental design, and causal inference techniques.
  • Experience with MLOps practices, including model deployment, monitoring, and lifecycle management in production environments.
  • Reside within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed.

Benefits
  • Comprehensive medical benefits coverage, dental plans and vision coverage.
  • Health care and dependent care spending accounts.
  • Employee and Family Assistance Program (EAP).
  • Employee discount programs.
  • Retirement plan with a generous company match.
  • Generous Paid Time Off, Sick, and Holidays
  • Family Leave (Maternity, Paternity)
  • Short- and long-term disability
  • Life insurance and accidental death & dismemberment insurance

Compensation Range
Compensation may vary depending on skills and experience.
Base Salary: $96,900 - $132,300
Diversity, Equity and Inclusion: At Canopy, we're on a mission to end theft from vehicles and revolutionize vehicle security by building cutting-edge technology. We will achieve this by prioritizing individuals and staying attuned to the evolving needs of our people, users, and industry trends. We foster a workplace culture that embraces diversity and authenticity, enabling us to flourish as a team of exceptional individuals working towards a common purpose. We gain a deeper understanding of our users' experiences by continuously improving our skills and expanding our knowledge. A more diverse, equitable, and inclusive Canopy leads to greater innovation and success.
Equal Opportunity: Canopy does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.

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