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Applied Data Analytics Jobs (NOW HIRING)

Siemens

Applied Data Scientist

Cincinnati, OH · On-site

$109K - $197K/yr

Excellent analytical and problem-solving skills, with a keen attention to detail. * Strong ... Familiarity with data integration, data cleaning, and linking methodologies. * Knowledge of MLOps ...

Siemens AG

$109K - $197K/yr

Excellent analytical and problem-solving skills, with a keen attention to detail. * Strong ... Familiarity with data integration, data cleaning, and linking methodologies. * Knowledge of MLOps ...

Siemens Mobility

Applied Data Scientist

Livonia, MI · On-site

$109K - $197K/yr

Excellent analytical and problem-solving skills, with a keen attention to detail. Strong ... Familiarity with data integration, data cleaning, and linking methodologies. Knowledge of MLOps ...

Siemens AG

Applied Data Scientist

Cincinnati, OH · On-site

$109K - $197K/yr

Excellent analytical and problem-solving skills, with a keen attention to detail. * Strong ... Familiarity with data integration, data cleaning, and linking methodologies. * Knowledge of MLOps ...

Clair

Senior Applied Data Scientist

New York, NY · On-site

$190K - $200K/yr

Learn more about us at getclair.com/about About the Role As an Applied Data Scientist on Clair ... Investigate and analyze credit performance, identifying root causes of model drift or unexpected ...

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Applied Data Analytics information

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How much do applied data analytics jobs pay per year?

As of Sep 14, 2026, the average yearly pay for applied data analytics in the United States is $129,468.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $174,000.00 per year, depending on experience, location, and employer.

What is applied data analytics?

An Applied Data Analytics job involves using data analysis, statistical methods, and machine learning techniques to extract insights and support decision-making in various industries. Professionals in this role work with large datasets, clean and preprocess data, and create visualizations to communicate findings effectively. They often use programming languages like Python or R, along with database tools such as SQL, to analyze trends and optimize business processes. Applied Data Analytics roles are found in sectors like healthcare, finance, marketing, and technology, helping organizations make data-driven decisions.

What does someone working in applied data analytics do?

Professionals in Applied Data Analytics typically spend their days collecting, cleaning, and analyzing large datasets to identify trends and patterns relevant to their organization’s goals. They use various statistical and machine learning techniques to build predictive models, generate visual reports, and present data-driven recommendations to stakeholders. Collaborating with cross-functional teams such as marketing, operations, and IT is common, ensuring data solutions are closely aligned with business needs. This dynamic role also involves continuous learning to keep up with evolving analytical tools and methodologies.

What are the key skills and qualifications needed to thrive in applied data analytics?

To thrive in Applied Data Analytics, you need strong analytical skills, proficiency in statistical methods, and typically a degree in data science, statistics, computer science, or a related field. Familiarity with programming languages such as Python or R, experience with data visualization tools like Tableau or Power BI, and knowledge of SQL are commonly required, along with relevant certifications such as Certified Analytics Professional (CAP). Strong problem-solving abilities, effective communication, and a knack for translating complex data into actionable insights set standout professionals apart. These skills are crucial for transforming raw data into meaningful solutions that support informed business decisions and drive organizational success.

Is data analytics a good career?

Applied Data Analytics is a growing field with strong demand for professionals skilled in data analysis, statistical methods, and tools like SQL, Python, or R. It offers opportunities across various industries, competitive salaries, and potential for career advancement, making it a viable and rewarding career choice.
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Applied Data Analytics jobs near you
Infographic showing various Applied Data Analytics job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $129,468 per year, or $62.2 per hour.

Staff Applied Data Scientist

Austin, TX • On-site

Steadily Insurance Company
See more jobs at Steadily Insurance Companyexternal

Full-time

Re-posted 18 days ago

Job description

Job Summary:
Steadily is a fast-growing company that manages over $20 billion in risk and is seeking a Staff Applied Data Scientist to join their Engineering team. In this role, you will identify and evaluate trends across large data sets and build, evaluate, and deploy machine learning models to improve product outcomes and operations.
Responsibilities:
• Design, build and evolve data sets and models with an emphasis on scalability, quality and maintainability, identifying the appropriate technique and approach to meet the needs of the business. Focus areas could be estimating risk at the property level, how to accurately assess property costs and using aerial image analysis or modelling techniques to identify individual attributes that feed into other models.
• Own and lead exploration and implementation of new areas of science application in our product ecosystem to better predict risk both on a per-insured level and in aggregate across the entire portfolio.
• Write clean, maintainable R/Python code, setting a high bar for quality and adherence to best practices.
• Partner closely with Engineering, Product, Operations and Business teams to design reliable solutions across systems.
• Provide excellent metrics and visibility into model quality, bias and performance to assess how it’s helping the business ensure a high bar of scientific rigor and evaluation.
Qualifications:
Required:
• 5+ years experience applying Data Science methods to production problems.
• Ability to dive into a complex codebase without too much spin-up.
• Experience as a team lead is a plus.
• Write clean, maintainable R/Python code, setting a high bar for quality and adherence to best practices.
• Partner closely with Engineering, Product, Operations and Business teams to design reliable solutions across systems.
• Provide excellent metrics and visibility into model quality, bias and performance.
Preferred:
• Actuarial experience, or experience applying models to risk evaluation and aggregation problems.
• Experience in vision photo analysis.
Company:
We built Steadily to serve landlords who want their insurance to work like other modern tools they love: fast and affordable with excellent service. Founded in 2020, the company is headquartered in Beaverton, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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