Product Data Scientist focused on building analytics that help teams understand behaviour, measure impact, and make better decisions.

I work across SQL, Python, statistics, forecasting, and BI to turn messy data into clear metrics, reusable analysis, and decision-ready products.

• Focus areas: Product analytics • Forecasting • Experimentation/statistical thinking • Usage intelligence • Self-serve analytics
• Tools: SQL • Python • Power BI • R • Applied ML/NLP
• Based in: Toronto, Canada

A portfolio project focused on report usage forecasting, behavioural analytics, and decision support for analytics adoption.

• Forecast usage patterns and detect engagement decline
• Model report, user, and page-level behaviour
• Combine analytics engineering, semantic modelling, and forecasting
• Explore how GenAI can support insight generation on top of usage data

→ Repo: report-usage-forecasting

Product-style analysis across traffic, conversion, customer behaviour, and business performance.

• Metric definition and business logic
• Funnel and performance analysis
• SQL for decision-oriented product questions

→ Repo: ecommerce-sql-portfolio

A reproducible statistics project showing how to test for differences across segments.

• Kruskal–Wallis for ordinal outcomes
• Chi-square for categorical relationships
• Post-hoc analysis to identify what is driving differences

→ Repo: survey-age-group-analysis

An end-to-end NLP project using topic modelling and an interactive Shiny app.

• Text preprocessing and LDA topic modelling
• Exploratory analysis of manifesto themes
• Interactive communication of model outputs

→ Repo: sa-political-manifesto-text-analysis

I am intentionally building a portfolio that demonstrates how I:

1. define business and product questions clearly
2. structure data into useful analytical models
3. analyse behaviour with SQL and Python
4. apply statistics or forecasting where it improves decision-making
5. communicate insights through dashboards, write-ups, and reusable projects

• Power BI / stakeholder delivery: maven_analytics_crm_sales_challenge
• Automation: gmail-mail-analysis
• Geospatial visualisation: interactive-map-python

I am especially interested in roles and projects at the intersection of:

• Product Data Science
• Analytics Engineering
• Forecasting and behavioural analytics
• Experimentation and causal thinking
• GenAI-enabled analytics workflows

I also write about analytics, data science, and practical portfolio-building:

• Medium: @masego_m

• LinkedIn: masego-modibane