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Data Science Jobs in Warren, MI (NOW HIRING)

Data Scientist

Plymouth, MI · On-site

$90 - $130/hr

Bachelor's degree in Data Science, Computer Science, Information Systems, Finance, Quantitative Methods, Statistics, Engineering, or a related discipline; an equivalent combination of education and ...

New

Data Scientist

Sterling Heights, MI · On-site

$50 - $58/hr

Bachelor's Degree in Data Management, Data Science, Math, Statistics or equivalent Education Preferred: Master's Degree in mathematics, statistics, business, engineering, physical/applied sciences ...

New

Leads data science projects from end-to-end, collaborating with cross-functional stakeholders, identifying business requirements, gathering data, researching analytics solutions, and integrating ...

Leads data science projects from end-to-end, collaborating with cross-functional stakeholders, identifying business requirements, gathering data, researching analytics solutions, and integrating ...

Leads data science projects from end-to-end, collaborating with cross-functional stakeholders, identifying business requirements, gathering data, researching analytics solutions, and integrating ...

Bachelor's in Data Management, Data Science, Math, Statistics Rate: $52 to $62 per hour (W2 contract non-benefitted, No PTO - ever hour worked is an hour paid) * Responsible for designing, building ...

... data science solutions. Lead Data Scientist architects, defines, and design the data science solution, and works with Data Scientist, Associate Data Scientist, and other business analysts to ...

Bachelor's in Data Management, Data Science, Math, Statistics Rate: $52 to $62 per hour (W2 contract non-benefitted, No PTO - ever hour worked is an hour paid) * Responsible for designing, building ...

You'll be joining our RXA Data Science team, a group dedicated to leveraging advanced analytics, predictive modeling, and machine learning to drive smarter marketing and business decisions. As Lead ...

You'll be joining our RXA Data Science team, a group dedicated to leveraging advanced analytics, predictive modeling, and machine learning to drive smarter marketing and business decisions. As Lead ...

Data Scientist

Detroit, MI · On-site

$120 - $170/hr

Data Scientist Role Summary OneMagnify's Data Scientists sit at the intersection of client strategy ... BA/BS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or a related ...

Showing results 21-40

Data Science information

See Warren, MI salary details

$35.2K

$115.3K

$184.6K

How much do data science jobs pay per year?

As of Aug 9, 2026, the average yearly pay for data science in Warren, MI is $115,280.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,500.00 and $127,700.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
What are the most commonly searched types of Data Science jobs in Warren, MI? The most popular types of Data Science jobs in Warren, MI are:
What are popular job titles related to Data Science jobs in Warren, MI? For Data Science jobs in Warren, MI, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Warren, MI look for? The top searched job categories for Data Science jobs in Warren, MI are:
What cities near Warren, MI are hiring for Data Science jobs? Cities near Warren, MI with the most Data Science job openings:
Infographic showing various Data Science job openings in Warren, MI as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, 4% Hybrid, and 16% Remote job distribution, with an average salary of $115,280 per year, or $55.4 per hour.

Data Scientist

Socket.dev

Plymouth, MI • On-site

$90 - $130/hr

Other

Posted 3 days ago

New


Job description

Job Title: Data Scientist

Department: Finance

Accountability: This Position Reports to the Senior Manager, Financial Planning & Analytics

We are building a next-generation analytics capability at the intersection of data, finance, operations, and strategy. The Data Scientist will support this effort by developing practical, scalable analytics, machine learning, and AI-enabled solutions that improve decision-making, strengthen reporting accuracy, and enhance business performance. This role combines data engineering, database design, statistical modeling, business intelligence, and process improvement to transform complex structured and unstructured data into timely, meaningful insights.

Working closely with Finance, Operations, IT, and other business stakeholders, the Data Scientist will gather requirements, define analytical approaches, build and validate models, automate data workflows, and deliver reporting tools that support efficient and effective business operations.

This is an excellent opportunity for an early-career professional with approximately 3-5 years of relevant experience who is highly analytical, technically capable, business-minded, and motivated by the opportunity to apply emerging AI technologies to real-world business challenges.

Primary Responsibilities:
  • Partner with Finance, Operations, IT, and functional leaders to understand business objectives, document requirements, assess current-state processes, and recommend data-driven solutions that improve efficiency, accuracy, and decision-making.
  • Design, develop, test, and maintain analytical models, predictive tools, reporting datasets, and AI-enabled solutions using Microsoft, SQL, Python/R, LLM, and related technologies.
  • Build, maintain, and optimize ETL/ELT pipelines that ingest, cleanse, transform, and validate data from multiple internal and external sources, including structured and unstructured datasets.
  • Develop dashboards, recurring reports, self-service analytics tools, and executive-level visualizations that translate complex data into clear, actionable business insights.
  • Apply machine learning, statistical analysis, forecasting, classification, optimization, and other advanced analytical methods to support planning, performance management, operational improvement, and strategic initiatives.
  • Provide technical guidance for data and analytics initiatives, ensuring solutions align with business priorities, data governance expectations, security practices, documentation standards, and scalable architecture principles.
  • Support enterprise-level data workflows, system interfaces, third-party software integrations, and modernization efforts, including evaluating legacy system risks and recommending long-term improvements.
  • Troubleshoot data quality, database, reporting, software, and infrastructure issues; optimize SQL queries, report performance, and data refresh processes; and elevate complex matters to vendors or internal stakeholders as needed.
  • Conduct code reviews, validate analytical outputs, promote reusable development practices, and help establish standards for data definitions, model documentation, testing, version control, and deployment.
  • Communicate findings, recommendations, risks, and tradeoffs clearly to technical and non-technical audiences, ensuring stakeholders understand both analytical results and practical business implications.
Job Requirements
  • Minimum of 3 years of experience in data analysis, data science, systems analysis, business intelligence, financial analytics, or a related role; experience applying ML/AI concepts in a business environment strongly preferred.
  • Bachelor’s degree in Data Science, Computer Science, Information Systems, Finance, Quantitative Methods, Statistics, Engineering, or a related discipline; an equivalent combination of education and relevant experience may be considered.
  • Strong foundation in SQL, relational databases, data warehousing, data modeling, data validation, and workflow orchestration.
  • Demonstrated analytical and problem-solving ability, including the capacity to evaluate ambiguous business issues, identify root causes, and propose practical technical solutions.
  • Ability to collaborate effectively with cross-functional stakeholders, end users, IT partners, and third-party vendors to deliver high-quality, sustainable analytics and system solutions.
  • Strong communication skills, including the ability to explain technical concepts, analytical assumptions, model outputs, and business recommendations in a clear and audience-appropriate manner.
  • Strong time-management, organization, and prioritization skills, with the ability to work independently, manage multiple concurrent initiatives, and meet deadlines in a dynamic environment.
  • High attention to detail and a commitment to producing accurate, reliable, repeatable, and well-documented work.
  • Working understanding of accounting, finance, and business operations terminology, including bookings, shipments, sales versus revenue, COGS, OpEx, debits, credits, and related reporting concepts.
  • Working knowledge of ERP transaction flows, preferably within Microsoft Dynamics NAV/Business Central; experience with manufacturing, distribution, or inventory-related data is helpful.
Technical Requirements
  • Advanced proficiency with Microsoft-based data, reporting, and development technologies, including SQL Server and related database tools.
  • Hands-on experience with machine learning and AI concepts, including model development, evaluation, automation, prompt-based or LLM-enabled workflows, and responsible use of AI outputs.
  • Strong experience with relational database design, SQL development, stored procedures, triggers, query optimization, indexing strategies, and performance tuning.
  • Proficiency with at least one scripting or statistical programming language, such as Python, R, or a comparable tool, for data processing, automation, modeling, and analysis.
  • Strong preference for hands-on experience with Power BI, including dataset design, DAX, report development, dashboard publishing, refresh management, and performance optimization; comparable visualization tools may be considered.
  • Experience with Git or other version control systems; familiarity with CI/CD practices for data pipelines, analytics assets, reports, or software development preferred.
  • Working knowledge of Access, Oracle databases, Syspro ERP, or related enterprise applications preferred.
  • Knowledge of data storage strategies, partitioning, indexing, data retention, data quality controls, and governance considerations a plus.
  • Demonstrated ability to translate complex business requirements into scalable technical designs, data models, reports, integrations, and automation solutions.
  • Experience integrating ERP, financial, operational, or other enterprise-grade systems with reporting, analytics, or data warehouse environments.
  • Understanding of software security, access controls, testing practices, model validation, peer review, release management, and documentation standards.
Work Environment – Office-Based Role (PA/OH/MI/MN/IN locations possible)
  • This role is primarily performed in a professional office environment and requires regular collaboration with cross-functional business partners. Occasional access to manufacturing, warehouse, or production areas may be required; applicable safety protocols and personal protective equipment requirements must be followed.

Prepared by: Human Resources

Approved by: Senior Manager, FP&A

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