Job Title:

Data Scientist




Toronto , ON

Who we are

Join Scene+ and be part of Canada's most robust lifestyle loyalty program with over 13 million members and growing! We are a trusted brand, driven by the belief that there's always something to look forward to with rewards for every kind of life. Our goal is to become Canada's favourite loyalty program by nurturing our Members with rewards their way. 

We're the exciting joint venture of Cineplex, Empire, and Scotiabank, blending the energy, optimism, and atmosphere of a startup with the funding of three major players. With over 80 team members and plans to grow more, we're an emerging, responsive company. We offer collaboration, accountability, challenges, and rewards to everyone who joins us.

Our motto is "Love what's next," and we believe it applies to your career too. Join us to help evolve the program, collaborate with amazing teams, and love what lies ahead.

Who we need

Reporting to the Senior Manager, Machine Learning and Data Science, we are looking for a Data Scientist to join our Data Science team. You will play a critical role in building out a forecast methodology to predict and strategically act on our membership growth. You will gain insights into our members, where they are coming from, and why they join. By analyzing data trends, you'll project monthly, quarterly, and yearly member acquisition. You will leverage data analysis, statistical modelling, and predictive analytics to forecast the behaviour and utilization of loyalty and rewards points within our organization, directly shaping our future success. 

This is a hybrid role with the requirement to work in-office five days over two weeks.

What's in it for you:

Ownership. We are a data science-driven company, and our membership is growing exponentially. You will be part of a fun, driven, small but scaling team that operates like a startup. We are adaptable, collaborative, and fast-paced, undertaking exciting transformational growth and optimizing our processes to be best in class. Your work will provide insights to drive planning for accelerated membership growth, uncover the hidden risks and trends, and optimize the member experience. 

Future forward impact. You'll be part of a future-forward team that values authenticity and invites fresh perspectives. This is an opportunity to take ownership of the forecasting process and work both independently and alongside data scientists, drawing from vast amounts of member and partner data. You will have the opportunity to support the team at leadership and owner presentations.

Anticipation. With giants in banking, grocery, and entertainment as our owners and partners across various categories like travel, shopping and dining, this is an opportunity to gain exposure across a wide range of sectors. With over 30% of our team promoted within the last year, we have a proven history of supporting the development of our people. You will gain exposure to fraud analytics and have the chance to grow in data science and more.

In this role, you will:

  • Analyze. You will ensure we pick the right data points to act on, identifying key engagement and potential disengagement indicators. You will write queries and build models to draw on vast amounts of internal and external data to gain an understanding of historical membership growth, member profiles, loyalty usage, points redemption, member behaviour, and transactional patterns. 
  • Forecast. You will develop accurate forecasting models based on historical data and market trends. You will use statistical techniques, machine learning, and predictive analytics to anticipate member behaviour and point redemption patterns.
  • Focus on applying insights. You will read the metrics, draw conclusions, make predictions, and share insights to guide planning, resource allocation, and strategic development. You will identify key trends, anomalies, and insights to inform forecasting models and strategies. Based on your forecasting, you will collaborate cross-functionally to recommend changes to our membership program to enhance member engagement and retention.
  • Report. You will create comprehensive reports and presentations to communicate forecasting results, insights, and recommendations to key stakeholders and senior management. You will translate complex data findings into easily understandable insights for non-technical stakeholders.
  • Learn. You will stay updated on industry best practices, advancements in loyalty program analytics, and emerging technologies to enhance forecasting methodologies and approaches.

You bring:

  • The experience. You may be a data scientist or forecast analyst from retail, banking, loyalty or another industry where you have developed skills in interpreting and integrating information from multiple internal and external sources. You are comfortable with all aspects of the analytics process, including managing many datasets, analyzing and ensuring data quality, generating and validating key insights, and influencing business decisions. You can drill down to the details, obtaining the right level of specificity to predict outcomes and support strategic objectives and recommendations.
  • The technical skills. You have worked in or alongside a data science team and you have a programming background. You love learning about new approaches and continuously seek answers to satisfy your curiosity. You can work with terabytes of data using tools such as Python, PySpark, and SQL to define query parameters, access large sets, conduct analyses, and gain insights. You can leverage predictive analytics, build forecasting models, generate recommendations based on trends, and present data connections effectively.
  • The integrity. You hold yourself and the organization you work for to the highest standards of accountability. You are detail-oriented and can balance competing priorities. You look for gaps and identify opportunities to introduce processes to increase efficiencies and build capacity.
  • The interpersonal skills. You have professional communication and relationship-building skills. You can build trust, articulate your recommendations, and influence decisions across any level of the organization. You have a deep respect for diverse backgrounds and perspectives.

Why work for Scene+? The best of all worlds. We offer:

  • Perks. Enjoy a competitive salary and benefits package, performance-based bonuses, and extra rewards from our owners, including discounted rates on mortgages, banking, movies, and groceries.
  • Transparency. Our strategic focus comes from our owners, along with funding and infrastructure support. The creative approach and direction is Scene+'s to run with. 
  • Warmth. We're nurturing an authentic culture of relationship building, knowledge sharing, and creativity. As we continue to grow and work together, everyone is invited to share ideas for fun with the team.
  • The future. We are all about living in the moment while looking towards the future. Because to us, the only thing more exciting than today is tomorrow.

What you can expect from our interview process:

  • A virtual interview with a Talent Advisor discussing your interest in the role and the company and how you will make an impact as our new Data Scientist.
  • An interview with the Senior Manager, Machine Learning and Data Science and a member of the Data Science team to learn about our current process and future plans. You will be able to share your insights and expertise and have time to ask questions about the company and the role.
  • An interview with the Director, Data Science and the SVP, Data Analytics to discuss how your data-driven approach and analytics knowledge lines up with the role and the team. It's a chance to ask questions about the company's growth trajectory and our owner relationships.


If you have 70% of what we're looking for and 100% authenticity and passion, express your interest here.


Please contact us by email and let us know what accommodations or assistance we can provide you during the application process.

At Scene+, we're committed to diversity, equity, and inclusion. We strive to integrate these values into everything we do, from our partners and offers to our teams and interactions. We welcome and appreciate candidates from diverse backgrounds, including women, persons with disabilities, Black, Indigenous and People of Colour (BIPOC), the LGBTQ2SIA+ community, and other equity-seeking groups.


Posted 2024-03-06

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