Michael Hartnett

As the lone Data Analyst, I was responsible for driving business value through data-driven insights through leveraging reporting that touched across multiple business functions

• Worked cross functionally with multiple departments, spanning from eCommerce, Engineering, Manufacturing, Branding/Design by providing data insights through customized reporting and continuous data-driven ad-hoc analysis
• Oversaw the Amazon specific sales channel and generated substantial year-over-year revenue growth through developing data supported budgets and goals. Provided full level data analysis and inventory recommendations to develop maximal strategy for driving purchases while increasing profits
• Implemented new data-centric processes that helped support the foundations for business decisions and relied on Python to automate and develop these processes.

• A key player in understanding every aspect of Criteo’s complex Retail Media business with an exceptionally broad view of Criteo’s business with a focus on US Brands (Demand side)
• Conducted ad-hoc analyses for top US Brands to identify root cause of ad performance issues, missed opportunities and areas of improvement to drive business growth (integration, inventory expansion and etc.)
• Proactively identified and collected analytical, tooling and reporting needs from Commercial stakeholders (Customer Success Management and Technical Solutions teams); developed self-service tools to answer these needs using Tableau, Python, VS Code (example: implemented a forecasting tool to predict potential business opportunities for brands and partners)
• Provided client or industry insights and presented as appropriate to internal teams throughout the organization and to Criteo clients externally (example: created Quarterly Consumer Electronics focused market insight presentations for internal teams to leverage in our business decisions and sales opportunities)

• Participated in a full-time immersive Data Science course, completing in-class projects, hackathons, and personal projects focused on real-world applications of data science principles and best practices
• Developed a portfolio of individually and collaboratively focused in-class projects, including: Project: Ames Housing Data: Predicted sale prices of homes utilizing regression modeling
• Project: Natural Language Processing Subreddit Classification And Sentiment Analysis: Classified reddit posts through NLP models and VADER sentiment analysis
• Group Project: Covid-19 Impact and Socioeconomic Relationship: Determined demographics and states disproportionately affected by Covid-19 pandemic with unsupervised machine learning

• Performed market analysis via rental databases to determine the most viable and attractive markets which will generate highest revenue for our brokerage
• Monitored current market trends and examining what type of client may be looking at a particular time of the cycle (i.e
• Students, professionals, families etc.)

• Core role focused on analyzing the financial reporting provided from of our partners on a quarterly basis and accurately translating them into our proprietary database
• Presented and prepared a benchmarking report/tool that was utilized extensively by our marketing team to present to potential clients regarding the success and health of our funds
• Prepared finalized reports summarizing the quarterly health and progress of upwards to 20-30 HarbourVest funds
• Monitored and entered the cash flow of distributions and capital calls designated by our firm as well as our partners on a daily basis