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
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.).
Requirements:
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.
Develop executive-ready dashboards, reports, and presentations.
Collaborate with product-facing teams to support data-driven decision-making and workflow optimization.
Job description
About Brillio:
Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.
Lead Data Analyst
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
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.
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