What a data scientist does
A data scientist uses statistics, programming and business knowledge to find patterns in data and build models that support decisions. Typical projects include forecasting demand, predicting customer churn, segmenting customers, testing pricing or product changes and measuring the effect of marketing. A data scientist frames the question, explores and cleans the data, chooses an appropriate method and communicates the findings along with their limitations.
The best data scientists are useful, not just technically impressive. They pick methods that fit the question, tell you how confident they are and know when a simple analysis is enough. Finch screens candidates for statistical grounding, Python or R skills, experience with real business data and the ability to present to non-technical audiences, so the people you interview can deliver work your organization will use.
Typical responsibilities
- Work with stakeholders to define questions and measures of success
- Explore, clean and prepare data from multiple sources
- Build statistical and machine learning models for forecasting, classification or segmentation
- Design and analyse experiments such as A/B tests
- Present findings, assumptions and limitations to decision-makers
- Hand off models to engineering teams for production use where needed
Qualifications and credentials
- A degree in statistics, mathematics, computer science, economics or a related field; many roles prefer a graduate degree
- Strong Python or R skills, plus SQL
- Grounding in statistics, experimental design and common machine learning methods
- Experience with tools such as pandas, scikit-learn and Jupyter notebooks
- Ability to visualize and present results clearly
Who hires a data scientist
- Banks, insurers and investment firms
- Retailers, consumer brands and e-commerce businesses
- Telecom and media companies
- Health care and life sciences organizations
- Consulting and analytics firms
Where we recruit data scientist candidates
We fill data scientist roles for employers across Toronto and the GTA, including North York, Scarborough, Etobicoke, Vaughan, Markham, Richmond Hill, Mississauga, Brampton, Oakville, Burlington, Oshawa and Pickering, and for employers across Canada. GTA employers can meet us at our North York office by appointment.
What Finch checks before you meet a candidate
- Statistical understanding, discussed through past projects rather than definitions alone
- Experience with messy, real-world business data
- Python or R and SQL skills suited to your environment
- Communication of results and uncertainty to non-technical audiences
- Examples where their work changed a business decision
Interview questions to ask
- Tell me about an analysis that changed a decision. What did the business do differently?
- How would you measure whether a new loyalty program actually increased sales?
- When have you told a stakeholder that the data could not answer their question?