Senior Data Scientist

TriNet•Atlanta, GA

7h•$100,800 - $189,000•Onsite

About The Position

The Senior Data Scientist has an intimate knowledge of business objectives and works with leadership to provide data science solutions that apply to cross functional teams roadmap. They will develop and code software programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Incumbents are tasked with identifying meaningful insights from large data and metadata sources; and interpreting and communicating insights and findings from analysis and experiments to product, service, and business managers. The senior data scientist will mentor team members to cultivate the skills and knowledge necessary to contribute to business needs and create a data driven culture. This role will prepare and deliver results to stakeholders and facilitate the deployment of models to production systems.

Requirements

Master's Degree or equivalent experience preferred
Typically 5+ years of experience
Strong knowledge of statistical analysis, machine learning, predictive modeling, and data science methodologies.
Proficiency in Python and SQL, with experience using machine learning and analytics tools and libraries.
Experience developing, deploying, and monitoring analytical models and data science solutions.
Ability to work with large, complex datasets using cloud-based and modern data platforms
Strong analytical and problem-solving skills, with the ability to translate business needs into actionable insights and technical solutions.
Ability to independently manage complex projects and make sound decisions regarding analytical approaches and model design.
Experience conducting experimentation, model validation, and performance measurement.
Effective communication and presentation skills, with the ability to explain technical concepts to both technical and non-technical audiences.
Ability to build collaborative partnerships across teams and provide guidance and mentorship to less experienced team members.
Knowledge of data governance, privacy, security, and responsible AI practices.
Experience with data visualization and reporting tools such as Tableau, Power BI, or similar platforms.
Demonstrated ability to manage multiple priorities in a fast-paced environment while maintaining professionalism, integrity, and confidentiality.

Responsibilities

Design, develop, validate, and deploy statistical models, machine learning solutions, and advanced analytics to address complex business challenges.
Translate business requirements into analytical approaches, model outputs, and actionable recommendations.
Perform exploratory data analysis, feature engineering, model development, and performance evaluation with minimal guidance.
Identify data gaps and recommend additional data sources to improve analytical outcomes.
Evaluate modeling tradeoffs and select appropriate methodologies based on business needs, scalability, and model performance.
Stay current on emerging data science, machine learning, and AI technologies and apply them when appropriate.
Lead the execution of complex data science projects from problem definition through implementation, monitoring, and optimization.
Develop project plans, timelines, and milestones to ensure successful delivery of analytical solutions.
Perform model testing, validation, and performance monitoring to maintain solution effectiveness and reliability.
Identify and resolve analytical, data quality, and model performance issues.
Recommend improvements to data science processes, tools, and model development practices.
Partner with business stakeholders, product teams, and technical teams to define requirements and develop data-driven solutions.
Apply business knowledge and analytical expertise to solve operational and strategic challenges.
Present data-driven recommendations that support decision-making and business objectives.
Collaborate across teams to deliver scalable and impactful analytical solutions.
Effectively communicate analytical findings, model results, and technical concepts to technical and non-technical audiences.
Prepare and maintain documentation, reports, and presentations to support knowledge sharing and solution adoption.
Identify risks, assumptions, and requirements gaps and recommend practical solutions.
Provide guidance, coaching, and knowledge sharing to junior data scientists and analysts.
Contribute to the adoption of data science best practices, modeling standards, and governance processes.
Support a collaborative culture focused on continuous learning, innovation, and operational excellence.
Perform other duties as assigned.
Comply with all company policies, procedures, and standards.