Data Science Specialist in Minnesota Career Overview

As a Data Science Specialist in Minnesota, you will engage in analyzing complex data sets to derive meaningful insights that can drive decision-making for organizations across various sectors. Your role is essential in today's data-driven landscape, as businesses and institutions increasingly rely on data to enhance their operations, improve customer experiences, and guide strategic initiatives.

Key Responsibilities:

  • Collecting and cleaning large data sets to ensure accuracy and relevance.
  • Developing predictive models and algorithms to analyze trends and forecast outcomes.
  • Visualizing data findings using charts, graphs, and dashboards to communicate insights effectively.
  • Collaborating with cross-functional teams to identify data needs and strategic opportunities.
  • Staying current with industry trends and technologies to leverage new tools and methodologies.

Industry Importance:

  • Organizations of all sizes recognize the potential of data-driven decision-making to gain competitive advantages.
  • Data Science Specialists play a vital role in translating raw data into actionable strategies that can optimize resources and enhance performance.
  • Your insights can lead to innovations, cost savings, and improved customer satisfaction, all of which contribute to an organization's overall success.

In Minnesota, the demand for Data Science Specialists continues to rise as businesses from healthcare, finance, technology, and other sectors seek to harness the power of data. Your expertise will make you a valuable asset as companies aim to stay ahead in a rapidly evolving market landscape.

Data Science Specialist Salary in Minnesota

Annual Median: $116,810
Hourly Median: $56.16

Data sourced from Career One Stop, provided by the BLS Occupational Employment and Wage Statistics wage estimates.

Required Education To Become a Data Science Specialist in Minnesota

To become a Data Science Specialist, you will typically need to complete relevant educational programs and training that provide a strong foundation in data analysis and management. Here are the common degree programs that align with this career path:

  • Data Analytics: A degree in Data Analytics focuses on interpreting complex data sets. This program generally includes coursework in statistical analysis, database management, and data visualization techniques.

  • Data Science: Pursuing a degree in Data Science prepares you for a comprehensive understanding of data handling and statistical methods. The curriculum typically covers machine learning, programming, data mining, and data engineering.

  • Bioinformatics: If you have an interest in the intersection of biology and data science, a degree in Bioinformatics may be suitable. This program often involves learning about biological data analysis, programming, and algorithms tailored to biological contexts.

  • Computational Biology: This degree focuses on the use of computational techniques to solve biological problems. You will study algorithm development, statistical methods, and bioinformatics tools, aimed at processing biological data.

  • Information Science Studies: A degree in Information Science Studies emphasizes the management of information and data systems. This program usually teaches you about information retrieval, data management, and human-computer interaction.

Each of these degree programs provides essential knowledge and training that will be beneficial in your career as a Data Science Specialist. Advanced degrees, such as a master's or Ph.D., may enhance your expertise and job prospects in this field.

Best Schools to become a Data Science Specialist in Minnesota 2024

University of Maryland Global Campus

Adelphi, MD

In-State Tuition:$7,488
Out-of-State Tuition:$11,976
Admission Rate:N/A
Graduation Rate:19%
Total Enrollment:55,838

University of Maryland-College Park

College Park, MD

In-State Tuition:$9,695
Out-of-State Tuition:$37,931
Admission Rate:45%
Graduation Rate:89%
Total Enrollment:40,792

Rutgers University-New Brunswick

New Brunswick, NJ

In-State Tuition:$12,900
Out-of-State Tuition:$30,600
Admission Rate:66%
Graduation Rate:84%
Total Enrollment:50,637

Pennsylvania State University-Main Campus

University Park, PA

In-State Tuition:$19,286
Out-of-State Tuition:$38,102
Admission Rate:55%
Graduation Rate:83%
Total Enrollment:50,028

University of Illinois Urbana-Champaign

Champaign, IL

In-State Tuition:$14,542
Out-of-State Tuition:$35,122
Admission Rate:45%
Graduation Rate:85%
Total Enrollment:56,916

University of Maryland-Baltimore County

Baltimore, MD

In-State Tuition:$9,056
Out-of-State Tuition:$25,820
Admission Rate:81%
Graduation Rate:70%
Total Enrollment:13,991
Data Science Specialist Job Description:
  • Conduct research into fundamental computer and information science as theorists, designers, or inventors.
  • Develop solutions to problems in the field of computer hardware and software.

Data Science Specialist Required Skills and Competencies in Minnesota

  • Statistical Analysis: You should be proficient in statistical methodologies and techniques. This includes understanding distributions, hypothesis testing, regression analysis, and statistical modeling.

  • Programming Languages: Familiarity with programming languages such as Python or R is essential. These languages are commonly used for data manipulation, analysis, and visualization.

  • Data Manipulation and Cleaning: Being skilled in data wrangling is important. This involves preparing and cleaning data to ensure its quality and usability for analysis.

  • Machine Learning: Knowledge of machine learning algorithms is necessary. You should understand supervised and unsupervised learning techniques, as well as how to implement and evaluate models.

  • Data Visualization: Ability to create visual representations of data to communicate findings effectively is key. Tools like Tableau, Matplotlib, or Seaborn can be particularly useful.

  • Database Management: Knowledge of SQL and database management systems is important for extracting and managing data stored in relational databases.

  • Big Data Technologies: Comfort with big data tools and frameworks such as Hadoop or Spark enables you to work with large datasets efficiently.

  • Business Acumen: Understanding the business context of the data you analyze helps you provide actionable insights that align with organizational goals.

  • Critical Thinking: You should be able to approach problems analytically and think critically to derive meaningful conclusions from complex datasets.

  • Communication Skills: Strong verbal and written communication skills are necessary for presenting findings and insights to both technical and non-technical stakeholders.

  • Collaboration: You should work well in team settings, as data science often involves collaboration with other data professionals, analysts, and business teams.

  • Adaptability: As a Data Science Specialist, being flexible and open to learning new technologies and methodologies can improve your effectiveness in this rapidly evolving field.

Job Duties for Data Science Specialists

  • Analyze problems to develop solutions involving computer hardware and software.

  • Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.

  • Assign or schedule tasks to meet work priorities and goals.

Technologies and Skills Used by Data Science Specialists

Analytical or scientific software

  • SAS
  • The MathWorks MATLAB

Development environment software

  • Apache Kafka
  • Oracle Java 2 Platform Enterprise Edition J2EE

Presentation software

  • Microsoft PowerPoint

Basic Skills

  • Listening to others, not interrupting, and asking good questions
  • Thinking about the pros and cons of different ways to solve a problem

People and Technology Systems

  • Figuring out how a system should work and how changes in the future will affect it
  • Thinking about the pros and cons of different options and picking the best one

Problem Solving

  • Noticing a problem and figuring out the best way to solve it

Job Market and Opportunities for Data Science Specialist in Minnesota

The job market for Data Science Specialists in Minnesota is robust and expanding, reflecting national trends and the specific needs of local industries. Here are some key aspects to consider:

  • Growing Demand: Organizations across multiple sectors, including healthcare, finance, retail, and technology, increasingly rely on data-driven decision-making. As a result, there is a significant demand for Data Science Specialists who can analyze complex datasets and extract actionable insights.

  • Diverse Industries: Minnesota is home to various industries that rely heavily on data science. Notable sectors include:

    • Health Care: Health systems and organizations leverage data analytics to improve patient outcomes and streamline operations.
    • Retail: Companies employ data science to optimize supply chains, enhance customer experiences, and personalize marketing strategies.
    • Finance: Financial institutions utilize data analysis for risk management, fraud detection, and investment strategies.
  • Growth Potential: The job market for Data Science Specialists is experiencing substantial growth, with many companies actively seeking professionals to fill this role. The increase in data generation and the emphasis on digital transformation are significant factors driving job creation in this field.

  • Geographical Hotspots: Certain areas in Minnesota stand out as hubs for data science opportunities:

    • Minneapolis-St. Paul: The Twin Cities are a central location for technology firms, startups, and established corporations that require data expertise. This region hosts numerous networking events and data science meetups, fostering collaboration and professional growth.
    • Rochester: As home to the Mayo Clinic, Rochester presents unique opportunities for data science specialists in the health care sector, focusing on health data analytics and research.
    • Duluth: Emerging tech companies in Duluth are beginning to make strides in data-driven services, expanding the scope for specialists in this area.
  • Networking and Professional Development: Numerous local organizations and chapters of national groups focus on data science, providing avenues for networking and professional development. Engaging with these communities can lead to job opportunities and collaborative projects.

As the need for skilled Data Science Specialists continues to rise, the Minnesota job market presents numerous opportunities for those looking to advance their careers in this dynamic field.

Additional Resources To Help You Become a Data Science Specialist in Minnesota

  • Data Science Central
    A community for data science professionals where you can find articles, webinars, and resources relevant to the field.
    Website: Data Science Central

  • Kaggle
    An online platform for data science competitions that provides datasets for practice and a learning community. You can improve your skills by participating in challenges.
    Website: Kaggle

  • Coursera
    Online courses from various universities on data science topics, including machine learning, data analysis, and statistical techniques.
    Website: Coursera Data Science

  • edX
    Offers professional certificates and MicroMasters programs in data science from renowned institutions such as MIT and Harvard.
    Website: edX Data Science

  • Towards Data Science
    A Medium publication featuring articles written by data science practitioners sharing knowledge, tutorials, and career advice.
    Website: Towards Data Science

  • The Data Science Association
    An organization that provides professional development resources, networking opportunities, and ethical guidelines for data science practitioners.
    Website: Data Science Association

  • Analytics Vidhya
    An online community that offers tutorials, articles, and job opportunities in data science and analytics.
    Website: Analytics Vidhya

  • American Statistical Association (ASA)
    A professional association that provides resources, networking, and educational opportunities for statisticians and data scientists.
    Website: American Statistical Association

  • GitHub
    A platform to explore open-source data science projects, share your work, and collaborate with others in the field.
    Website: GitHub

  • DataCamp
    An interactive learning platform that focuses on data science through online courses and hands-on coding challenges.
    Website: DataCamp

  • Springboard
    Offers a data science career track with mentorship from industry experts to guide you through practical projects.
    Website: Springboard Data Science

  • AI + Data Science Meetups in Minnesota
    Check platforms like Meetup.com for local groups focused on data science and AI to network with peers and participate in workshops.
    Website: Meetup

  • shrm.org - Society for Human Resource Management
    To understand the workforce trends related to data science roles and the skillsets companies are seeking.
    Website: Society for Human Resource Management

Frequently Asked Questions (FAQs) About Data Science Specialist in Minnesota

  • What qualifications do I need to become a Data Science Specialist in Minnesota? Generally, a bachelor’s degree in a related field such as computer science, statistics, mathematics, or data science is required. Many professionals also pursue a master’s degree or relevant certifications to enhance their skills and job prospects.

  • What programming languages should I learn as a Data Science Specialist? Proficiency in programming languages such as Python, R, and SQL is essential. Additionally, familiarity with other languages like Java or Scala can be beneficial for certain roles.

  • What tools and software are commonly used in data science? Common tools include statistical software packages like R and SAS, data manipulation tools like Pandas, machine learning libraries such as Scikit-learn, and visualization tools like Tableau or Power BI. Familiarity with cloud platforms like AWS or Google Cloud can also be advantageous.

  • What types of industries employ Data Science Specialists in Minnesota? Data Science Specialists find opportunities in various industries, including finance, healthcare, retail, education, and technology. Minnesota is home to companies across these sectors, providing diverse job options.

  • Is experience required to enter the field of data science? While entry-level positions may be available, relevant internships, projects, or coursework can significantly enhance your candidacy. Gaining practical experience through internships or research projects is often recommended.

  • What key skills should I develop to succeed in data science? Important skills include statistical analysis, data visualization, machine learning, and data wrangling. Additionally, strong critical thinking and problem-solving abilities, along with effective communication skills, are essential.

  • How important is networking for a career in data science? Networking plays a vital role in advancing your career. Engaging with professionals in the field through meetups, conferences, and online platforms like LinkedIn can help you discover job opportunities and gain insights.

  • What is the job outlook for Data Science Specialists in Minnesota? The job outlook for Data Science Specialists is favorable, with a growing demand for data-driven decision-making across various sectors. This trend is likely to continue as businesses increasingly rely on data analysis for strategic planning.

  • How much can I expect to earn as a Data Science Specialist in Minnesota? Salaries for Data Science Specialists can vary based on experience, education, and the specific industry. As of 2023, entry-level positions may start around $70,000 annually, while experienced professionals can earn upwards of $100,000 or more.

  • Are there any professional organizations for Data Science Specialists in Minnesota? Yes, organizations such as the Minnesota Data Science Meetup and local chapters of national organizations like the American Statistical Association (ASA) and the Data Science Association offer networking opportunities and resources for professionals in the field.