Analytics Engineer

Data Scientist - Product Analytics & Experimentation Job Summary We are seeking a Data Scientist to drive product growth, customer acquisition, and funnel optimization initiatives through advanced analytics, experimentation, and data-driven decision making. This role partners closely with Product, Marketing, Engineering, Design, and Business stakeholders to define key success metrics, measure product performance, identify growth opportunities, and influence strategic decisions. The ideal candidate brings deep expertise in product analytics, A/B testing, causal inference, SQL, statistical modeling, and forecasting , along with experience building scalable reporting and measurement frameworks.

Key Responsibilities Product Analytics & Growth Measurement Define, measure, and optimize key funnel and product performance metrics. Identify opportunities to improve end-to-end customer journey performance. Drive insights that influence product strategy and business outcomes. Develop KPI frameworks and measurement methodologies for new initiatives.

Experimentation & Data Science Design, execute, and evaluate A/B tests and controlled experiments. Develop experiment instrumentation, success metrics, reporting, and statistical analysis. Perform significance testing, causal inference analysis, and impact measurement. Conduct ad hoc exploratory, directional, and causal analyses to support business decisions.

Reporting & Analytics Engineering Automate KPI reporting and performance monitoring processes. Build and maintain dashboards, data pipelines, and self-service analytics solutions. Develop scalable reporting capabilities for product and business stakeholders. Improve data quality, measurement reliability, and reporting efficiency.

Cross-Functional Collaboration Partner with Product Managers, Marketers, Engineers, Designers, and Business Leaders. Translate complex analyses into actionable recommendations. Support product development, growth initiatives, and strategic planning efforts. Drive a culture of experimentation and data-driven decision making.

Modeling & Forecasting Develop forecasts and predictive models using time series and statistical techniques. Analyze trends, customer behavior, and business performance drivers. Support strategic planning through advanced analytics and scenario modeling.

Required Qualifications Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Business Analytics, Mathematics, Economics, or a related quantitative field. Strong experience in Data Science, Product Analytics, or Business Analytics roles. Advanced SQL skills and experience working with large-scale datasets. Hands-on experience designing and analyzing A/B tests and experimentation frameworks. Strong understanding of statistics, hypothesis testing, and causal inference methodologies. Experience building dashboards, reporting frameworks, and KPI measurement systems. Strong analytical thinking and problem-solving abilities. Proven ability to work cross-functionally and influence stakeholders through data.

Preferred Qualifications Experience in Financial Technology (FinTech), Payments, Digital Commerce, E-commerce, Consumer Technology, or Growth Analytics environments. Experience with customer acquisition, referral programs, retention, or growth funnels. Knowledge of time series forecasting and predictive analytics techniques. Familiarity with data pipeline optimization and analytics engineering concepts. Experience with AI-assisted workflows, Generative AI tools, or machine learning applications. Experience developing self-service analytics and experimentation platforms.

Technical Skills Required SQL, Product Analytics, A/B Testing, Experiment Design, Statistical Analysis, Causal Inference, Data Visualization, KPI Development, Funnel Analytics, Dashboard Development, Data Modeling, Business Analytics

Preferred Python, R, Machine Learning, Time Series Forecasting, Growth Analytics, Analytics Engineering, Generative AI, Predictive Modeling, FinTech Analytics, Customer Journey Analytics

For applications and inquiries, contact:View email address on us.fitly.work