Data Scientist

6 months ago

Toronto, Canada Plusgrade Full time

Travel is not just about the destination; it's about every memory made along the way. We are dedicated to shaping the future of travel by partnering with 200+ airline, hospitality, cruise, passenger rail, and financial services companies to create new, meaningful revenue streams through incredible customer experiences. Rooted in our core values of being ambitious, innovative, and collaborative, we are driven to continuously raise the bar, exceed expectations, and bring out the best in everyone, fostering a culture where we believe we are better together, working towards an extraordinary future in travel. Come help us transform everyday travel into extraordinary experiences.

**ABOUT THE ROLE**:
We are seeking a full-time Data Scientist to join our Toronto team on a permanent basis.

Fueled by ever-expanding data sources across our product, partner, and member network, Plusgrade is creating a world of advanced analytics that are real-time, automated, always on, and always learning. This collective intelligence is our unique offering—it enables us to drive unparalleled member engagement and program economics for our partners.

Reporting to the Team Lead, Data Science, the Data Scientist will research, develop, and deliver best-in-class modelling solutions, including pricing optimization models and personalized offer assignments. They will leverage data science methodologies to solve complex problems and provide guidance while coordinating with other data scientists to achieve the goals of all areas of the business.

**WHAT YOU WILL BE DOING**:

- Responsible for designing, building, and implementing machine learning models for marketing campaigns to ensure the campaign meets business objectives.
- Utilize optimization and simulation expertise to research and recommend the best approaches for solving our business problems.
- Build pragmatic, scalable, and statistically rigorous solutions that can be applied across products and partners by developing statistical and machine learning methodologies.
- Continuously improve the models and algorithms through research, testing, and iteration.
- Elevate the data science discipline by aligning with other data scientists on best practices, automation, and standardization of all advanced analytical solutions, end-to-end modelling processes, and offer optimizations. Drive execution through fast iteration.

**YOU ARE SOMEONE WITH**:

- Proficiency with machine learning, optimization, big data, predictive analytics, time series analysis, recommender systems, reinforcement learning, and visualization tools with a solid understanding of best practices in data science.
- Strong programming skills with SQL, Python (and/or R), and associated machine-learning packages.
- Comprehensive and solid data knowledge and skills, with a good understanding of data warehousing. Experience with handling large, imperfect data is an asset.
- Experience with implementing ML solutions on the cloud (e.g., Snowflake, AWS) preferred.
- Ability to communicate/present complex ideas/analysis in a concise, business-friendly manner
- Experience with ML automation and productionizing machine learning solutions is an asset.
- Natural curiosity to solve problems and find meaning in complex data sets & customer behaviour analysis.
- Experience with ML automation and productionizing machine learning solutions is an asset.
- Masters or equivalent experience in a quantitative field (e.g. Statistics, Math, Computer Science, Engineering or other related fields).

**WHAT YOU’LL LOVE ABOUT US**:
\uD83C\uDFE6 RRSP/401(k) Matching

\uD83C\uDFE5 Comprehensive Health Plans

\uD83D\uDCC5 Flexible Paid Time Off

✈️ Travel Experience Credit

\uD83E\uDDD8 Annual Wellness Credit

\uD83E\uDD57 Team Events and Monthly Lunches

\uD83D\uDCBB Home Office/Commuter Credit

\uD83C\uDF05 Work From Anywhere Program

\uD83C\uDF7C Parental Leave Top Up

\uD83C\uDF0D Adventure Pass

**OUR PROCESS**:

- Recruiter Phone Interview
- Hiring Manager Interview
- Take-home Assessment or remote coding exercise (if applicable)
- Team Interview

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