Data Scientist

HireRight•Nashville, TN

40d

About The Position

About HireRight HireRight is the premier global background screening and workforce solutions provider. We bring clarity and confidence to vetting and hiring decisions through integrated, tailored solutions, driving a higher standard of accuracy in everything we do. Combining in-house talent, personalized services, and proprietary technology, we ensure the best candidate experience possible. We offer expertise from our regional centers across 200 countries and territories in The Americas, Europe, Asia, and the Middle East. Our commitment to get it right every time, everywhere, makes us the trusted partner of businesses and organizations worldwide. Overview We are seeking a highly analytical and detail-oriented Data Scientist to support data-driven decision-making across the organization. This role focuses on building predictive models, generating actionable insights, and translating complex data into clear business recommendations. The ideal candidate combines strong technical skills with business acumen and a collaborative mindset.

Requirements

Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related field or equivalent experience
2–3 years of experience in data science, analytics, or a related role.
Experience with Salesforce and CXone
Proficiency in Excel (pivot tables, formulas, charts)
Experience with BI tools (Tableau, Power BI, Looker, etc.).
Strong understanding of statistical concepts and model validation techniques.
Ability to communicate complex data clearly to non-technical stakeholders.
Strong analytical and problem-solving skills, with attention to detail and accuracy.
Knowledge of call center metrics, operations, and workforce management concepts.

Nice To Haves

Experience in contact center, operations, or high-volume environments.
Experience with A/B testing and experimentation frameworks.
SQL or database query experience.
Familiarity with call center platforms (e.g., Genesys, Five9, Avaya, NICE, Talkdesk, etc.).
Experience with forecasting, staffing models, or scheduling tools.
Ability to manage multiple reporting requests and prioritize deadlines.

Responsibilities

Develop, test, and deploy predictive and statistical models to support operational and strategic initiatives.
Perform exploratory data analysis to identify trends, anomalies, and opportunities.
Apply machine learning techniques (regression, classification, clustering, time series forecasting) as appropriate.
Evaluate model performance and iterate for accuracy and business impact.
Extract, clean, and transform data from multiple sources (SQL databases, APIs, flat files).
Build reproducible data pipelines and structured datasets for analysis.
Ensure data integrity, quality, and governance standards are upheld.
Translate analytical findings into clear, actionable recommendations.
Partner with WFM, operations, finance, and leadership teams to define analytical needs.
Support dashboard and reporting development in collaboration with BI resources.
Present findings to stakeholders in a concise, executive-ready format.
Identify automation opportunities to reduce manual reporting.
Recommend new tools, methodologies, or data sources to enhance insights.
Stay current with emerging data science techniques and best practices.