About Us
Great Place To Work® is the global authority on workplace culture. Our mission is to help every place become a Great Place To Work® for all. We give leaders and organizations the recognition and tools to create a consistently and overwhelmingly positive employee experience, fostering cultures that are proven to drive business, improve lives, and better society.
Our recognition is the most coveted and respected in the world for elevating employer brands to attract the right people. Our proprietary methodology and platform enable organizations to truly capture, analyze, and understand the experience of all employees. Our groundbreaking research empowers organizations to build cultures that retain talent and unlock the potential of every employee. Our coaches, content, and community connect the boldest leaders, ideas, and innovations in employee experience. Since 1992, our Certification™, Best Workplaces™ Lists, and global benchmarks have become the industry standard, built on data from more than 100 million employees in 150 countries around the world.
In 2021, Great Place To Work® was acquired by UKG (Ultimate Kronos Group.) As a leading global provider of HCM, payroll, HR service delivery, and workforce management solutions, UKG believes organizations succeed when they focus on their people. While Great Place To Work® will continue operating independently within the UKG family, our research and insights will help UKG differentiate its best-in-class HR, talent, and workforce management technology, and together we'll support every workplace to become great. UKG has 15,000 employees around the globe and is known for its inclusive and supportive workplace culture and best-in-class rewards and benefits.
Both UKG and Great Place To Work® are leading the change on what it means to be a Great Place To Work® for all, and we are proud to be Certified™ great workplaces!
About the Position
The Data Scientist IV reports directly to the Director, Global Recognition Operations.
We are seeking an innovative and solutions-oriented team player with an advanced understanding of statistics, AI, and data science techniques who loves to make their team’s work more efficient. This position sits on our Global Recognition & Research team and leverages advanced data science and machine learning skills to advance all aspects of Great Place To Work’s Best Workplaces list and research programs. The role’s primary mandate is to modernize the systems, methodologies, and workflows that protect list credibility and enable global recognition programs to scale with less manual effort, shorter cycle times, and lower key-person dependency. This role will collaborate closely with many other subject matter experts and stakeholders throughout our global business.
This role is a combination of a data scientist, technical requirements lead, process-improvement owner, and production-solution steward. You will not only analyze data and develop models but also translate complex business and methodology rules into technical solutions, improve the processes around them, and help ensure those solutions remain reliable and maintainable over time.
The work primarily involves complex employee survey and company-level data used for benchmarking, eligibility decisions, scoring, ranking, and research. The data is often drawn from multiple sources and requires careful matching, transformation, validation, and quality control. Many of the problems are less about building a single predictive model and more about designing robust, reproducible analytical systems that apply complex rules consistently and can be trusted at scale.
This is a remote role with travel of up to 5%.
Key Responsibilities
- Independently lead complex data science and technical-improvement projects from problem definition through implementation, delivering measurable improvements in business impact, efficiency, quality, scalability, and risk reduction.
- Develop, validate, document, and maintain the algorithms, scripts, statistical models, benchmarks, and data workflows used to produce global Best Workplace lists, independently diagnosing issues and making sound technical decisions related to data preparation, quality assurance, reproducibility, sensitivity testing, and methodology enhancements.
- Assess end-to-end list-production and global data-management workflows and lead improvements via automation, standardization, simplification, and scalable system solutions.
- Translate business and methodology needs into implementation-ready requirements, including process maps, data definitions, acceptance criteria, dependencies, test scenarios, controls, and measures of success; proactively resolve conflicting stakeholder needs and surface decisions, tradeoffs, and risks.
- Design and implement AI-enabled solutions, prototypes, and automations, independently determining the appropriate technical approach and partnering with Product, Tech, and business stakeholders when solutions require production engineering, infrastructure, system integration, or secure access.
- Ensure technical solutions remain reliable and sustainable by establishing appropriate documentation, testing, monitoring, support, and maintenance practices.
- Build alignment across technical and non-technical stakeholders by clarifying priorities, roles, tradeoffs, risks, and decisions, and by communicating technical concepts in accessible business language.
- Cross-train with the Principal Data Scientist to maintain coverage during peak periods.
Required Qualifications
- 5-7+ years of professional data science experience, with advanced expertise in machine learning, statistical modeling, algorithms, data transformation, AI-enabled solutions, and the development of applied insights or analytics-based solutions for business users.
- Advanced programming proficiency in Python, along with advanced SQL experience, including querying, reconciling, transforming, and validating large, complex, or incomplete datasets across relational, cloud, or other data platforms.
- Experience independently designing, automating, and supporting complex, business-critical data workflows, including APIs, data pipelines, cloud environments, workflow-automation tools, inherited code, and deployed AI-enabled solutions, with the judgment to make progress despite ambiguity or incomplete information.
- Experience owning the lifecycle of an internal analytical product or business-critical technical capability, from discovery and requirements through implementation, adoption, maintenance, enhancement, and retirement.
- Experience building data science or analytics solutions with production-readiness in mind, including applying software-engineering best practices (such as clean and modular code, version control, automated testing, code review, deployment, monitoring, model-performance and accuracy evaluation, safe change practices, third-party API updates, and troubleshooting production issues) or partnering with software engineers to turn prototypes into reliable, supported production solutions.
- Experience eliciting, analyzing, reconciling, and documenting business, functional, technical, data, and integration requirements, including process maps, workflow specifications, data definitions, user stories or use cases, acceptance criteria, test scenarios, and implementation documentation that technical and non-technical partners can use.
- Strong systems thinking, initiative, technical judgment, and problem-solving skills, with a demonstrated ability to independently structure complex problems, identify root causes and improvement opportunities, define future-state processes, make well-reasoned recommendations, and determine when to build directly, maintain an interim solution, or partner with Product and Tech.
- Demonstrated stakeholder-management, communication, and project-leadership skills, including the ability to build credibility with diverse partners; align stakeholders with different perspectives and priorities; clarify decision rights and ownership; manage expectations, dependencies, and competing demands; communicate progress, risks, and tradeoffs proactively; translate complex technical concepts for senior leaders and non-technical users; and work effectively in a collaborative remote environment while demonstrating commitment to Great Place To Work values, behaviors, and mission.
Preferred Qualifications
The strongest candidates may also bring experience in one or more of the following:
- Working with survey, employee experience, customer experience, market research, or other human-subjects data, particularly where sampling, measurement, benchmarking, or interpretation matter.
- Developing scoring, benchmarking, ranking, classification, or eligibility methodologies where analytical decisions have meaningful consequences for customers or other external stakeholders.
- Working with messy, multi-source organizational or entity-level data, including record matching, entity resolution, data reconciliation, validation, and quality assurance.
- Working in consulting, research, professional services, or another client-facing analytical environment, with experience translating ambiguous business questions into rigorous analytical solutions.
- Modernizing legacy analytical processes or inherited code, including reducing manual work and key-person dependencies while maintaining continuity and accuracy.
- Using R or maintaining/migrating R-based analytical workflows.
All job descriptions are written to accurately reflect the open job and include general work responsibilities. They do not present a comprehensive, detailed inventory of all duties, responsibilities, and qualifications required for the job. Management reserves the right to revise the job or require that other or different tasks be performed if or when circumstances change.
The pay range for this position is $153,985 to $219,362.50. The actual base pay offered may vary depending on skills, experience, job-related knowledge and work location. In addition to base pay, employees may be eligible to participate in a performance-based bonus plan and to receive restricted stock unit awards as part of total compensation. Learn more about UKG’s benefits and rewards at https://www.ukg.com/about-us/careers/benefits
Benefits
Here, we know that you’re more than your work. That’s why our benefits help you thrive personally and professionally, from wellness programs and tuition reimbursement to U Choose - a customizable expense reimbursement program that can be used for more than 200+ needs that best suit you and your family, from student loan repayment, to childcare, to pet insurance. Our inclusive culture, active and engaged employee resource groups, and caring leaders value every voice and support you in doing the best work of your career. Information about our comprehensive benefits can be reviewed on the careers site at https://www.ukg.com/careers.
Equal Opportunity Employer
Great Place To Work is an equal opportunity employer. We aim to create and foster a Great Place To Work For All. We evaluate qualified applicants without regard to race, color, disability, religion, sex, age, national origin, veteran status, genetic information, and other legally protected categories.
View The EEO Know Your Rights poster
Great Place To Work/UKG participates in E-Verify. View the E-Verify posters here.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Disability Accommodation in the Application and Interview Process
For individuals with disabilities that need additional assistance at any point in the application and interview process, please email US_Recruiting@greatplacetowork.com.