Senior Data Scientist
- 1303 Yonge St, Toronto, ON M4T 1X3, Canada
Cineplex (TSX:CGX) is a top-tier Canadian brand that operates in the Film Entertainment and Content, Amusement and Leisure, and Media sectors. A leading entertainment and media company, Cineplex welcomes over 70 million guests annually through its circuit of theatres and location based entertainment venues across the country. In addition to being Canada’s largest and most innovative film exhibitor, Cineplex also operates successful businesses in digital commerce (CineplexStore.com), food service, alternative programming (Cineplex Events), cinema media (Cineplex Media), digital place-based media (Cineplex Digital Media), amusement solutions (Player One Amusement Group) and an online esports platform for competitive and passionate gamers (WorldGaming Network). Additionally, Cineplex operates a location based entertainment business through Canada’s newest destination for ‘Eats & Entertainment’ (The Rec Room), and will also be opening new complexes specially designed for teens and families (Playdium) as well as exciting new sports and entertainment venues across Canada (Topgolf). Cineplex is a joint venture partner in SCENE, Canada’s largest entertainment loyalty program.
Proudly recognized as having one of the country’s Most Admired Corporate Cultures, Cineplex employs approximately 13,000 people in its offices across Canada and the United States. To learn more visit Cineplex.com or download the Cineplex App.
Cineplex is currently recruiting for the position of Senior Data Scientist, reporting directly to the Director, Data & Analytics.
The purpose of the Senior Data Scientist position is to continue to drive Cineplex’s various lines of business forward leveraging deep insights obtained from data using advanced statistics/mathematics and machine learning methodologies.
From a broad perspective, this position will involve working with a wide variety of datasets to design and implement industry-leading models and analyses. The key to success in this role is the ability to work on and execute cross-functional projects from beginning to end. Further, this position will involve keeping pace of the latest industry trends in machine learning and AI and how they can be continuously applied to various lines of the business.
This position will serve the following use cases: (Note that this is not an exhaustive list, rather, part of being successful in this position will involve being able to dynamically add projects and workloads depending on current business needs):
Digital & Omni-Channel: Product Rationalization, Inventory Management, Channel Management, Strategic/Dynamic Pricing, Strategic Consumer:
- Data Science Skills Required: Kernel density estimation, variable importance measures, stochastic differential equations/Fokker-Planck methodologies, K-means/hierarchical and other unsupervised clustering techniques, knowledge of 1-3D CNNs, and NLP as applied in deep learning algorithms.
Customer Personalization/Curation: Campaign optimization, Marketing automation, and recommendations/curations:
- Data Science Skills Required: classification algorithms that utilize unbalanced datasets (neural networks, gradient-boosted trees)
- Writing algorithms that can be updated continuously as live data is ingested to provide up-to-date recommendations.
Sales and Merchandising: Demand and audience forecasting/projections:
- Data Science Skills Required: Multi-regression algorithms (neural networks, gradient-boosted trees, other appropriate algorithms)
- Time-dependent probability distribution modeling
Operations/Supply Chain: Optimal resource allocation/scheduling, workflow automation, infrastructure rationalization
- In-depth knowledge of solving optimization problems: linear and non-linear programming using KKT, Lagrange multipliers and similar methods. In particular, such problems will require using data science/machine learning methodologies in combination with implementing numerical solvers for various optimization problems.
Software / Technology Skills Required
To be successful in this role, the data scientists will need to have in-depth knowledge of existing industry-standard ML platforms such as R and Python, and AI platforms built in these environments such as: Microsoft’s Cognitive Toolkit (CNTK), Keras and PyTorch. Further, to solve optimization problems, the data scientist should have knowledge of numerical solvers available in R such as optim() and optimx(), and have knowledge of solving optimization problems in Mathematica and/or MATLAB.
Further, it must be recognized that this position involves being at the fore-front of new technologies in the ML/AI world. Since most of our data science projects are based off Microsoft technologies such as ML Server (Python Server + R Server) which are increasingly being implemented in successive versions of SQL Server and PowerBI, the data scientist will have to constantly be up-to-date with these latest trends and implementations.
Working With Other Members of The Analytics Team
The current analytics team consists of experts in data visualization/interaction, data engineers who maintain the data structures and queries in SQL Server and who operationalize the R/Python scripts for large-scale production, and a forecasting and pricing analytics expert.
This role will involve continuous and close collaboration with all of the aforementioned groups. In particular, the main role of the Principal Data Scientist will be to prototype/design algorithms, and implement them using the appropriate software libraries. They will then work closely with the database/data engineering team to implement these algorithms for “productionalization” so that they can be run “at scale” and on a regular schedule. The data scientist will also make use of live data provided by this team to build algorithms that can make use of live data for the most accurate models possible.
This role will also involve close collaboration with the forecasting and pricing analytics data scientist. In particular, this role will function in two ways. Part of the time, the forecasting and pricing analytics data scientist will design a forecasting model of which the Principal Data Scientist will then help to implement in a “big data” setting in an efficient manner. The role will also function in the opposite direction as well. The Principal Data Scientist will also design/implement forecasting models which the forecasting and pricing analytics data scientist will manage and maintain on a regular basis.
Finally, this role will involve close collaboration with the data visualization team who will be responsible for implementing the user interface behind the various ML solutions for business consumption. This will either be in the form of the principal data scientist being responsible for handing over data in the form of tables in SQL Server of which the visualization team will make dashboards in PowerBI “from scratch” or taking over a rough dashboard/visualization created by the Principal Data Scientist to make it more appropriate for wide business consumption.
Interested applicants please apply today.
While we appreciate all interest, only those candidates selected for an interview will be contacted. As part of Cineplex Entertainment’s standard recruitment process, suitable candidate(s) will be required to undergo pre-employment screening as a condition of employment or promotion.
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