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Senior Insurance Data Analytics Jobs in Utah (NOW HIRING)

Experience in Property and Casualty insurance is strongly preferred. Key Responsibilities Data Modeling and Analytics Engineering * Design, build, and maintain analytical data models for reporting ...

We are seeking a Senior Analytics Engineer to play a key role in advancing Trove Brands' analytics ... This individual will help drive data governance, data quality, and scalable analytics solutions ...

I have an opportunity for "Data Analyst" and looking for a candidate who can join Immediately if ... Best Regards Syed Imran Sr Technical Recruiter 224-296-3522 | syed@navtechusa.com NAVTECH INC ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies ...

... analysis, and statistical methods for finding structure in large data sets. Roles and Responsibilities As a Sr Data Scientist, you will be part of a data science or cross-disciplinary team on ...

Showing results 21-40

Senior Insurance Data Analytics information

What are the key skills and qualifications needed to thrive as a senior insurance data analytics professional?

To thrive as a Senior Insurance Data Analytics professional, you need a strong background in statistics, data analysis, and domain knowledge of insurance, often supported by a degree in mathematics, statistics, or a related field. Expertise in data analytics tools such as SQL, Python, R, and experience with business intelligence platforms like Tableau or Power BI are typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex insights clearly set top performers apart in this role. These skills are crucial for driving data-driven decision-making, identifying business opportunities, and improving risk assessment and operational efficiency within insurance organizations.

What does a senior insurance data analytics professional do?

A Senior Insurance Data Analytics professional analyzes large datasets to help insurance companies make informed decisions about risk, pricing, claims, and customer behavior. They use statistical methods, data modeling, and business intelligence tools to uncover trends and insights that can improve operational efficiency and profitability. In addition to interpreting complex data, they often collaborate with other departments to develop data-driven strategies and may oversee or mentor junior analysts within the team.

What is the difference between Senior Insurance Data Analytics vs Insurance Data Analyst?

AspectSenior Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often with experience in insurance analyticsBachelor's in related field; entry to mid-level experience
Work EnvironmentSenior roles often involve leadership, project management, and strategic planning within insurance companiesFocus on data collection, analysis, and reporting under supervision or team guidance
Employer & Industry UsageUsed across insurance firms, especially in analytics, underwriting, and actuarial departmentsCommonly employed in insurance companies, focusing on data processing and reporting

Senior Insurance Data Analytics professionals typically have more experience, advanced skills, and leadership responsibilities compared to Insurance Data Analysts. While both roles require strong analytical skills and familiarity with insurance data, seniors often oversee projects, develop strategies, and mentor junior staff, whereas analysts focus on data analysis and reporting tasks.

What are some common challenges faced by senior insurance data analytics professionals when working with large and complex datasets?

Senior Insurance Data Analytics professionals often encounter challenges such as integrating data from multiple legacy systems, ensuring data quality and accuracy, and managing sensitive information in compliance with regulations. Additionally, translating complex analytical findings into actionable insights for non-technical stakeholders can be demanding. Overcoming these challenges requires strong technical skills, clear communication, and close collaboration with IT, underwriting, and actuarial teams.
What are the most commonly searched types of Insurance Data Analytics jobs in Utah? The most popular types of Insurance Data Analytics jobs in Utah are:
What cities in Utah are hiring for Senior Insurance Data Analytics jobs? Cities in Utah with the most Senior Insurance Data Analytics job openings:

AI & GenAI Data Scientist-Senior Associate

Pwc

Salt Lake City, UT

$77K - $202K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

New


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

25th of 72 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

Job Description & Summary

The Opportunity
As an AI & GenAI Data Scientist-Senior Associate, you will be at the forefront of transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Technology Consulting practice, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based solutions at scale. Your work will involve designing AI systems, data wrangling, and software implementation to enable the AI models to be useful and scalable.
As a Senior Associate, you will focus on building meaningful client connections and learning how to manage and inspire others. You will navigate increasingly complex situations, growing your personal brand and deepening your technical skills. You are expected to anticipate the needs of your teams and clients, delivering quality solutions. Embracing increased ambiguity, you will be comfortable when the path forward isn't clear, using these moments as opportunities to grow.
In this role, you will leverage advanced technologies and techniques to design and develop robust data solutions for clients. Your contributions will be crucial in transforming data into insights, driving business growth, and enabling informed decision-making.
Responsibilities
- Designing and implementing AI systems to transform raw data into actionable insights
- Developing and deploying scalable AI and Machine Learning solutions using advanced technologies
- Collaborating with clients to understand their data needs and deliver tailored solutions
- Utilizing programming languages such as Python and C++ to build robust data models
- Managing data pipelines and confirming data quality and integration across platforms
- Applying machine learning libraries like TensorFlow and Scikit-Learn to enhance model performance
- Conducting complex data analysis to inform strategic decision-making
- Leveraging natural language processing and text analytics for innovative AI applications
- Building and maintaining data infrastructure to support AI-driven automation
- Mentoring junior team members and fostering a collaborative work environment
What You Must Have
- At least a Bachelor's degree
- At least 2 years of experience
What Sets You Apart
- Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics, Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics, Data Processing/Analytics/Science, Artificial Intelligence and Robotics
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating proficiency in AI implementation and machine learning libraries
- Utilizing Python for complex data analysis and modeling
- Excelling in neural network design and reinforcement learning agents
- Applying natural language processing techniques for text analytics
- Leveraging TensorFlow and Scikit-Learn for deep learning projects

Travel Requirements

Up to 80%

Job Posting End Date

The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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