Senior Data Scientist

Socket.dev; Dunwoody (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

TriNet is seeking a Senior Data Scientist to apply data science solutions across cross-functional teams, developing algorithms and automated processes to cleanse and evaluate large datasets from multiple sources. The role involves mentoring teammates to foster a data-driven culture and delivering models to production with stakeholders.

The candidate will work to translate business requirements into analytics, design robust models, and stay current with AI technologies to drive business impact.

Qualifications

• Design, develop, validate, and deploy statistical models and ML solutions.
• Mentor team members to promote a data-driven culture.
• Deliver results to stakeholders and productionize models.

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.

Skills

Data science

Modeling

Stakeholder collaboration

Communication

Job description

TriNet is a leading provider of comprehensive human resources solutions for small to midsize businesses (SMBs). We enhance business productivity by enabling our clients to outsource their HR function to one strategic partner and allowing them to focus on operating and growing their core businesses. Our full-service HR solutions include features such as payroll processing, human capital consulting, employment law compliance and employee benefits, including health insurance, retirement plans and workers’ compensation insurance.
TriNet has a nationwide presence and an experienced executive team. Our stock is publicly traded on the NYSE under the ticker symbol TNET. If you’re passionate about innovation and making an impact on the large SMB market, come join us as we power our clients’ business success with extraordinary HR.
Don't meet every single requirement? Studies have shown that many potential applicants discourage themselves from applying to jobs unless they meet every single requirement. TriNet always strives to hire the most qualified candidate for a particular role, ensuring we deliver outstanding results for our small and medium-size customers. So, if you're excited about this role but your past experience doesn't align perfectly with every single qualification in the job description, nobody’s perfect – and we encourage you to apply. You may just be the right candidate for this or other roles.

A Brief Overview

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.

What you will do

• Data Science & Modeling

  • 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.

  Technical Delivery

  • 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.

  Collaboration & Business Partnership

  • 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.

  Communication

  • Effectively communicate analytical findings, model results, and