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Data Science Jobs in Portland, MI (NOW HIRING)

Delta Dental of Michigan

Data Scientist

Okemos, MI · Hybrid

To implement quantitative and predictive models, data science experiments using literate programming techniques such as Python Jupyter Notebooks, develop appropriate visualizations of data, curate ...

Delta Dental of Michigan

Data Scientist

Okemos, MI · On-site

To implement quantitative and predictive models, data science experiments using literate programming techniques such as Python Jupyter Notebooks, develop appropriate visualizations of data, curate ...

Auto-Owners Insurance

Data Scientist

Lansing, MI · On-site

Mathematics, Statistics, Computer Science, Physics, Operations Research, Economics, Electrical Engineering, etc.) * Proficiency in SQL or other data querying language * An understanding of ...

Amway Inc.

Cloud Data Engineer

Ada, MI

$92K - $113K/yr

Collaborating with analysts, data scientists, and business partners to understand data requirements * Implementing data quality, monitoring, and reliability practices * Leveraging modern developer ...

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All JobsData Science JobsData Science Jobs in Portland, MI

Data Science information

See Portland, MI salary details

$30.9K

$101K

$161.8K

How much do data science jobs pay per year?

As of Jul 20, 2026, the average yearly pay for data science in Portland, MI is $101,035.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,100.00 and $112,000.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

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 jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

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 work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

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.
More about Data Science jobs
What cities near Portland, MI are hiring for Data Science jobs? Cities near Portland, MI with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Portland, MI as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $101,035 per year, or $48.6 per hour.
Data Scientist

Data Scientist

Delta Dental of Michigan

Okemos, MI • Hybrid

Full-time

Medical, Dental

Posted 29 days ago

Job description

Job Title:

Data Scientist

Number of Positions:

1

Location:

Okemos, MI

Location Specifics:

Hybrid Position

Job Summary:

At Delta Dental of Michigan, Ohio, and Indiana we work to improve oral health through benefit plans, advocacy and community support, and we amplify this mission by investing in initiatives that build healthy, smart, vibrant communities. We are one of the largest dental plan administrators in the country, and are part of the Delta Dental Plans Association, which operates two of the largest dental networks in the nation.


At Delta Dental, we celebrate our All In culture. It's a mindset, feeling and attitude we wrap around all that we do - from taking charge of our careers, to helping colleagues and lending a hand in the community.

Position Description:

To implement quantitative and predictive models, data science experiments using literate programming techniques such as Python Jupyter Notebooks, develop appropriate visualizations of data, curate and prepare data using appropriate programmatic and non-programmatic data transformation techniques, continuously learn new techniques and methods to improve data science outcomes.

Primary Job Responsibilities:

  • Develops and implements advanced statistical models using casual modelling, machine learning and optimization techniques.
  • Leads the team incorporating new Data Science techniques to enhance the organization's best practices.
  • Applies machine learning algorithms and predictive models to solve complex business challenges.
  • Designs and conducts data-driven experiments to validate findings and hypotheses.
  • Communicates insights and results to senior stakeholders and decision-makers.
  • Develops innovative approaches to data collection and validation, incorporating both structured and unstructured data sources.

Perform other related assigned duties as necessary to complete the Primary Job Responsibilities as described above.

#LI-Hybrid

Minimum Requirements:

Position requires a bachelor's degree in Computer Science, Mathematics, Statistics, or other quantitative field with a master's degree in Data Science, Business Analytics, Health Informatics, or related field preferred, and three years of experience working extensively with data. Knowledge of health or dental insurance, or of dental clinical practice preferred.

Position requires experience in statistical modeling methods, machine learning algorithms, supervised and unsupervised learning, and data mining techniques; proficiency with statistical software packages like SAS, R, or equivalent preferred; experience with programming languages, especially Python and SQL, or equivalent;
excellent communication skills and the ability to clearly and concisely communicate complex information to a variety of audiences, both technical and non-technical; the ability to collaborate in a team.

The company will provide equal employment and advancement opportunity within the context of its unique business environment without regard to race, color, religion, gender, gender identity, gender expression, age, national origin, familial status, citizenship, genetic information, disability, sex, sexual orientation, marital status, pregnancy, height, weight, military status, or any other status protected under federal, state, or local law or ordinance.

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