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Data Science Assistant Jobs in Wisconsin (NOW HIRING)

Innovizant LLC

Data Scientist

Madison, WI · On-site

... data science, data engineering and decision science to provide winning actionable insights ... Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which ...

Innovizant LLC

Data Scientist

Madison, WI

... data science, data engineering and decision science to provide winning actionable insights ... Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which ...

KOHLS

Data Scientist I

Menomonee Falls, WI

... data science team and cross-functional partners to solve business challenges and promote data-driven decision making with advanced data analysis and machine learning. What You'll Do * Assist in ...

Innovizant LLC

Spark Expert (Direct Client)

Madison, WI · On-site

Innovizant made up of exceptional data scientists and domain experts with a great experience in Our ... Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which ...

CTech Manufacturing

Data Engineer

Schofield, WI · On-site

$114K - $137K/yr

... Assist in transitioning ETL workflows into scalable, efficient ELT processes Work with SQL Server ... Associate's degree or higher in Computer Science, Data Science, Information Systems, or a related ...

Qualysoft

... Data-Science- und KI-Projekten. Rahmenbedingungen Start: ASAP Laufzeit: Ende 2026, Verlangerung ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Howard

Research Assistant

Downing, WI

$19.25 - $26.50/hr

The candidate should be well-informed about the scientific method, human subjects research, and data analysis using computational and statistical techniques. The Research Assistant will assist in ...

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Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a Data Science Assistant, and why are they important?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data science assistants can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is not a barrier if you develop the necessary competencies and stay current with industry trends.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What is a data scientist assistant?

A data scientist assistant supports data scientists by collecting, cleaning, and analyzing data, often using tools like Python or R. They help prepare reports, build models, and may need knowledge of statistics and data visualization to contribute effectively to data projects.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret results, develop models, and make strategic decisions. Data scientists are increasingly required to work alongside AI tools, focusing on complex problem-solving, model development, and domain expertise. Continuous learning and proficiency in programming languages like Python and tools such as machine learning frameworks remain essential for the role.

Which is better, DS or CS?

For a Data Science Assistant role, both Data Science (DS) and Computer Science (CS) provide valuable skills; DS focuses on data analysis, modeling, and visualization, while CS emphasizes algorithms, programming, and software development. The choice depends on the specific job requirements and your career goals, but familiarity with programming languages like Python or R and understanding of data tools are essential in both fields.
What are the most commonly searched types of Data Science jobs in Wisconsin? The most popular types of Data Science jobs in Wisconsin are:
What are popular job titles related to Data Science Assistant jobs in Wisconsin? For Data Science Assistant jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Science Assistant jobs in Wisconsin look for? The top searched job categories for Data Science Assistant jobs in Wisconsin are:
Data Science Assistant jobs near you
Data Scientist

Data Scientist

Innovizant LLC

Madison, WI • On-site

Full-time

Posted 12 days ago

Job description

Company Description
Innovizant LLC (headquartered in Chicago, USA) is a leading-edge, global IT Services organization with Sales and delivery offices in Asia. Innovizant LLC, is a Full-service IT provider, focused on delivering Innovative and value driven business analytical solutions leveraging data science, data engineering and decision science to provide winning actionable insights assisting our financial services clients banking, Insurance and credit union business in achieve their business goals.
Innovizant made up of exceptional data scientists and domain experts with a great experience in Our financial services industry solutions include Credit Risk insights, Customer Churn analysis, Customer segmentation, Fraud detection, Asset and Liability analysis, channel optimization analytics, Financial Advisor Network Analytics and product bundling analytics.
Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which provided pre-delivered data strategies for the office of Chief Data Officer), BASEL-PRO (for achieving compliance with industry requirements of Basel-BCBS239,) and SmartCECL (Risk mitigation strategies by predicting default and loss given a default)
With data becoming the new 'oxygen' of businesses, many data science consulting firms have evolved in recent times, and they are also contributing the best of their solutions to the modern-day clients. It means today; you can easily find a solution for data sciences. However, the biggest challenge during managing this data comes across in the terms of 'Value Realization'. The true measure of success is to be able to put the data science insights into actionable events.
Many organizations have ended up spending a significant chunk of their analytics budget in some implementing data sciences solution - with minimal to no returns.
Job Description
Role: Data Scientist
Location: Madison, WI
Full Time (Direct Hire)
Job description
• 5+ Years of total experience and 2-4 years of in-depth and superlative experience in Data Science.
• Experience in Statistical modeling.
• Candidate will be helping the client to lead this process or improve upon the program.
• Extremely proficient in Data Analysis, data wrangling, model development, software development, A/B Testing, Back Testing.
• Extremely efficient in Python and R.
• Extremely efficient in identifying right analytics model methods and using them. Gradient Boosting, Decision Tree, Regression - are absolutely must.
• Exposure to Insurance (especially consumer Insurance/Retail Insurance) is a minor edge.
• MS in AI/Data Science would also be a plus.
Qualifications
Data Science, Analysis, Python, R, Statistical Modeling, Machine Learning
Additional Information
Thanks & Regards,
Aditya Prakash / Resource Manager / Innovizant LLC
Phone : 630-685-1260
aditya.prakash(AT)innovizant(DOT)com

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