Technical Analyst III (Part-Time)

A client with Kforce is seeking a Part-Time Technical Analyst III to join their team in Mountain View, CA. Summary: We are seeking an experienced Technical Analyst IV to join our team. The ideal candidate will bring a mix of technical expertise, business acumen, and strategic influence. This role involves owning the full analytics lifecycle - from data extraction, modeling, and dashboarding to experimentation and storytelling. The candidate will collaborate cross-functionally across Product, Marketing, Design, and Engineering to generate actionable insights that guide product strategy, optimize performance, and measure business impact. Key Responsibilitiesz;

• Lead end-to-end data workflows: design, development, testing, deployment, and visualization
• Develop data pipelines, ETL processes, and analytical frameworks leveraging SQL and Python/R
• Design and execute A/B tests, apply causal inference, and evaluate marketing and product interventions
• Build predictive models and perform statistical analyses to uncover trends and opportunities
• Create and maintain interactive dashboards and reports for key performance tracking and storytelling
• Conduct data validation, robustness testing, and cross-source verification for data quality and reliability
• Synthesize insights into compelling narratives that drive executive and partner decision-making
• Collaborate with engineering and data teams to define requirements for scalable data infrastructure
• Partner with business and marketing stakeholders to externalize data insights and support go-to-market initiatives
• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Economics, or related quantitative field
• 5-8+ years in applied data science, analytics, or related field (experience in product, marketing, or B2B analytics preferred)
• Strong proficiency in SQL, Python, or R for data manipulation, analysis, and modeling
• Experience with data visualization tools (e.g., Tableau, Power BI, Looker)
• Familiarity with modern data platforms (e.g., BigQuery, Snowflake, Databricks, AWS)
• Knowledge of experimental design (A/B testing, multivariate testing) and causal inference techniques
• Comfort with statistical and machine learning models such as ARIMA, Chow-Lin, and XGBoost

• Excellent data storytelling, communication, and stakeholder management skills
• Ability to translate complex analyses into actionable recommendations
• Proactive, independent, and adaptable in fast-paced environments