Lead AI Operations Data Analytics - R01562072

Primary Skills

• Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio

Specialization

• Data Science Advanced: Data Analyst

Job requirements

• 1. JTBD Analysts (USA): 

  The ideal candidate will demonstrate expertise in A/B testing implementation, exploratory data analysis (EDA), quantitative and qualitative analysis, along with the ability to translate ambiguous inputs into structured frameworks and actionable insights.
  Key Responsibilities
  • Support AI-enabled operational execution, reporting, and analytics initiatives across business functions.
  • Deliver high-quality analytical outputs within defined timelines for strategic and operational projects.
  • Design and implement A/B testing experiments, including hypothesis creation, experiment setup, statistical validation, and result interpretation.
  • Conduct comprehensive Exploratory Data Analysis (EDA) to uncover trends, patterns, and opportunities.
  • Perform advanced quantitative analysis using statistical techniques and modeling methods.
  • Synthesize qualitative data (customer feedback, interviews, survey responses) into structured, measurable insights.
  • Manage throughput and real-time triage workflows, ensuring prioritization of high-impact initiatives.
  • Collaborate with product-facing teams to support data-driven decision-making and workflow optimization.
  • Convert ambiguous or loosely defined business problems into clear analytical frameworks and structured problem statements.
  • Develop executive-ready dashboards, reports, and presentations.
  • Demonstrate strong business writing and storytelling skills to communicate complex findings in a concise and impactful manner.
  Required Qualifications
  • Experience in Data Analytics, preferably in CX, product analytics, or operational analytics environments.
  • Proven hands-on experience in:
    • A/B testing implementation and experimentation frameworks
    • Hypothesis testing and statistical validation
    • Exploratory Data Analysis (EDA)
    • Quantitative and qualitative analysis
    • Experience supporting AI-driven or operational analytics initiatives.
    • Proficiency in SQL and at least one programming language (Python or R).
    • Strong experience with data visualization and reporting tools (Tableau, Power BI, Looker, etc.).
    • Demonstrated ability to manage high-volume workstreams and real-time analytical triage.
    • Excellent written communication and business storytelling skills.
    • Ability to work aligned to North America business hours.