Data Scientist - Product Analytics & Growth Measurement *** Direct end client ***
Why This Role Stands Out
This hybrid role offers an exciting opportunity to directly impact product growth and strategy by leveraging advanced analytics and experimentation, perfect for a data scientist passionate about driving measurable results. You'll thrive here if you excel in SQL, statistical modeling, and A/B testing, collaborating with diverse teams to influence key business decisions. Apply now to join Projas Technologies and shape the future of their products!
Quick Overview
Job Description
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
Senior Data Scientist, Data Scientist, Product Analytics, Growth Analytics, Experimentation, A/B Testing, AB Testing, Multivariate Testing, Statistical Analysis, Causal Inference, Hypothesis Testing, SQL, Advanced SQL, Product Data Science, Business Analytics, Customer Analytics, Funnel Analytics, Conversion Optimization, KPI Development, Data Visualization, Dashboarding, Tableau, Power BI, Looker, Data Modeling, Analytics Engineering, Predictive Analytics, Forecasting, Time Series Forecasting, Machine Learning, Python, R, FinTech, Financial Technology, Referral Programs, Customer Acquisition, Growth Strategy, Product Metrics, Data Pipelines, Experiment Design, Decision Science, Customer Journey Analytics, Digital Products, Generative AI, Artificial Intelligence, AI-Assisted Workflows, Cross-Functional Collaboration, Data-Driven Decision Making, Product Growth, E-commerce Analytics, Consumer Analytics, Quantitative Analysis, Senior Analytics Consultant, Insights Analytics, Product Measurement, Statistical Modeling
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