Job Description

Overview

We are seeking a highly motivated and experienced Senior Business Data Analyst to join our GBSG CS Analytics Team. In this role, you’ll drive data-driven strategies that optimize both human-assisted support experiences and the broader end-to-end customer journey. By partnering with cross-functional teams, you’ll deliver insights that enhance service design, improve operational efficiency, and elevate overall customer satisfaction. This is a unique opportunity to make a meaningful impact on both support experiences and strategic customer initiatives. If you’re passionate about shaping the future of customer success through data, we’d love to hear from you!

What you'll bring

6+ years of combined post-graduate academic and industry experience in data analysis and business intelligence
Advanced proficiency in SQL, “big data” technologies (e.g., Redshift, Spark, Hive, BigQuery)
Must have advanced proficiency in Qlik. Qlik certification is a big plus
Intermediate knowledge of designing experiments (A/B/n) and measuring their impact using descriptive and inferential statistical methods
Early understanding of Causal Inference methods (Propensity Score, DiD, Synthetic Control, etc..) and when to use them to answer key business questions
Knowledge of programming languages (e.g., Python, R) and building ML models (supervised and unsupervised)
Experience with AI/GenAI tools for automating tasks and building custom implementations is highly preferred
Strong data storytelling skills, with a proven ability to rapidly construct impactful visualization, communicate insights and influence leadership
Excellent communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical teams
Comfortable working in a fast-paced environment and have flexibility to shift priorities when needed
Bachelor’s degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics or related quantitative field; Master’s Degree preferred

How you will lead

Define KPIs and Success Metrics: Establish key business indicators for projects, ensuring alignment with company objectives and clear measures of success.
Strategic Recommendations: Provide actionable recommendations using diverse data sets and business knowledge, even when complete data is unavailable, to support strategic decisions.
Data Visualizations: Translate complex data into clear, accessible visualizations that help stakeholders understand key insights and make informed decisions.
Experimentation & A/B Testing: Design, execute, and analyze A/B tests and other experiments using a hypothesis-driven approach. Provide insights and recommendations based on test outcomes to optimize business strategies.
Predictive Analytics & Modeling: Develop predictive models and methodologies to uncover growth opportunities and support long-term business planning.
Enable Self-Serve Analytics: Define and implement standardized metrics, reports, and dashboards. Work with Data Engineering to ensure data quality and enhance real-time analytic capabilities.
AI/GenAI Integration: Collaborate with AI teams to integrate AI/GenAI solutions into business processes, enhancing efficiency and innovation.
Cross-Functional Collaboration: Partner with product, digital and customer support teams to identify opportunities, create data-driven strategies, and influence decision-making.
Stay Current with Industry Trends: Keep up with evolving trends and advancements in data analytics to drive innovation and continuously improve business processes.