Pedram Safaeifar

Context

Coordinate a multi-phase research initiative to generate market and stakeholder insights for residential water solutions.

What I Did

• Defined project scope, timeline, and key deliverables for the research initiative
• Coordinated internal stakeholders and external partners across multiple workstreams
• Structured the project into phases including research design, data collection, synthesis, and reporting
• Monitored progress and ensured alignment between technical, commercial, and research teams

Outcome

Delivered a structured insight program that produced actionable market intelligence and supported internal discussions on product opportunities and strategic priorities.

Objective

Investigate customer churn patterns for a streaming video startup to identify retention drivers and guide strategic focus toward the most promising user segments.

What I Did

• Analyzed overall churn trends since the company's inception
• Performed comparative churn analysis across distinct user segments
• Examined how consumer behavior differs between segments to identify growth opportunities
• Built reproducible SQL-based analytical queries for churn metrics

Tools

SQL, SQLite, Segment Analysis, Retention Metrics

Objective

Understand the key factors driving airline pricing dynamics and help identify optimal flight deals through comprehensive data exploration.

What I Did

• Analyzed pricing distributions across cabin classes and flight characteristics
• Investigated the impact of in-flight amenities, delays, and booking patterns on pricing
• Explored weekend vs. weekday and red-eye flight pricing variations
• Visualized trends using Seaborn and Matplotlib for clear insight communication

Tools

Python, Jupyter Notebook, Seaborn, Matplotlib

Objective

Predict sales patterns by analyzing historical data using time series methodologies and evaluating which models perform most effectively.

What I Did

• Conducted exploratory data analysis on sales data to identify trends and seasonality
• Applied time series forecasting techniques including ARIMA modeling
• Compared multiple machine learning approaches to identify optimal predictive models
• Evaluated model performance using accuracy metrics

Tools

R, Time Series Analysis, ARIMA, Prescriptive Analytics

Context

Support internal initiatives with structured data analysis and evidence-based insights.

What I Did

• Analyzed datasets related to product usage and market behavior
• Developed analytical dashboards to highlight patterns and trends
• Integrated quantitative analysis with qualitative insights

Outcome

Provided data-supported insights that informed internal discussions and initiative prioritization.

Context

Understand factors influencing adoption of residential water solutions across key European markets.

What I Did

• Designed and coordinated a structured research initiative involving multiple industry stakeholders
• Synthesized qualitative insights into key themes related to installation practices and purchasing dynamics
• Structured findings into clear insight areas and opportunity themes

Outcome

Generated strategic insights that informed internal discussions on product positioning and potential market opportunities.