• Design and implementation of BI architecture. Based on forpeople’s budget and requirements a data stack of Airbyte, Snowflake and Power Bi were chosen.• Create data pipelines to Snowflake, via airbyte, to be visualised Power BI. Included a mixture of sql databases, files and api calls.• Implemented data quality checks to help resolve incorrect data entries.• Develop a suite of reports, which merged multiple datasets, using advanced SQL and Power BI.

Data consultant experienced in Tableau , Power BI, Alteryx, SQL, Python and Databricks with exposure to machine learning. Advanced at ETL, analysis and visualisation.

• Geospatial project to determine how many transit miles would be saved when increasing the number of fulfilment stores to be used for online orders. Alteryx iterative macro was used to develop a prediction based on an actual months’ worth of orders. Orders were orchestrated according to stock on hand and drivetime distance.• Developed a weekly forecast, via databricks, using Spark and Python to predict the sales of 350k SKU’s across over 150+ stores. Spark was used to run parallel forecasts and bring the process speed down to 30 minutes. Both ARIMA and ETS models were utilised during this process.• Developed automated responses to chargebacks, via the Paypal API, using a combination of Alteryx and Python.• Reconciled stock, sales and cash data to ensure systems had matching data. Required connecting to Paypal and Klarna APIs as well as building a complex data model in Power BI.

• Lead analytics consultant on projects primarily involving Alteryx and Power BI.• Alteryx – Created complex ETL pipelines linking multiple datasets for reporting purposes. Implemented best practices for documentation and development.• Power BI – Designed templates to be used across multiple departments. Developed pricing as well as regulatory reports.

Project Saturn – Developing datasets, via Alteryx, required for a suite of IS&OP dashboards to be used by demand planners, finance and supply. Key functionalities have included the ability for users to insert dummy data, volume corrections and forecast growth predictions.

• Commercial pricing and Underwriting - Alteryx and Tableau Lead.• Alteryx -reverse engineered pricing models from SAS, VBA, XML and Tower Watson. ETL of large databases to create the data sets required for modelling and visualisation. Developed dynamic apps and macros to help the team automate pricing calculations and data extraction. Created and delivered training course.• Tableau – Dynamic KPI reports and investigatory dashboards to aid the entire department including directors. Implemented functional templates for dashboards and landing pages. Created and delivered 4 day training course.

• Fixed term contract Data School (4 months) and placements (18 months).• 4 months of intense Alteryx and Tableau training covering ETL, analysis, statistics, visualisation methods and best practices, machine learning. • Python and R training - Data visualisation, ETL, analysis and machine learning. Python ETL solutions to challenges on GitHub/ Drivetime analysis in Tableau with R• SQL training - Joins, unions, case statements and clauses such as group by.

• Data Science Product Services – Internal consultancy working directly with stakeholders.• Azure DevOps used for time and product management and utilised in an Agile, end-to-end, development environment.• Rebuilt a SQL a material forecast in Alteryx and visualised, in Tableau, its variables and various outputs for re-engineering and bug fixing purposes.

Proprietary trading of Asian handicap goal markets using my own in-play time decay algorithm within a complex Excel spreadsheet. The algorithm was created through the reverse engineering of software used by Betbutler.Improvement of spreadsheet efficiency through the implementation of macros, such as web scraping, via VBA.Development of trading algorithm through analysis of large historical datasets and previous results.

Managing in play and pre-game odds for all sports available on the site.Creating and pricing spread betting markets for all sports.Examination and altering of market prices available on the website.

Trading football matches in-play on Betfair with the companies bespoke software. Trading/hedging sports liabilities as well as the daily reconciliation of trades.Analysing client’s bets to determine the company’s future trading strategy.Researching and analysing historical football data to determine value bets.

Researching and analysing an extensive database of potential sponsorship clients worldwide.Producing detailed reports on companies who fit the clubs sponsorship criteria.

In depth analysis of bookmaker’s odds and historical football data to determine value bets for trading based on probability.Partaking in bi-weekly analyst meetings to discuss each analyst’s picks Writing detailed analysis betting selections to subscribers.