Data Scientist II

About Us:

At Quickplay, we believe in transparency, fairness, and collaboration while we passionately work on some of the toughest use cases in OTT video, focused on massive scale and resilience. If you aspire to be part of a high-performing, learning-oriented, and caring culture—you've landed on the right company. Our Data Science & Data Engineering team is expanding, and we're seeking a highly skilled Data Scientist II to drive critical analytical insights and shape our product strategy.

About the Role:

As a Data Scientist II at Quickplay, you will be a lead individual contributor primarily focused on designing, developing, and deploying advanced analytical and machine learning solutions to address complex business problems. You will play a crucial part in translating high-level business questions into rigorous data science initiatives, guiding the team on methodology, and influencing key product and strategic decisions with your expertise in data analysis, model building, and compelling communication.

Work Model:

Ability to work onsite in our Toronto office three days per week — Tuesday, Wednesday, and Thursday.

Key Responsibilities:

• Lead the end-to-end execution of complex data science projects, from identifying strategic business opportunities to delivering actionable insights and deployed models.
• Design and implement advanced AI/ML models and statistical analyses to understand customer behavior, predict churn, optimize engagement, and drive business growth across large, complex datasets.
• Collaborate closely with Product Management, Engineering, and Analytics teams to define key customer KPIs, integrate data science solutions into products, and ensure data-driven decision-making.
• Provide thought leadership and technical guidance on various aspects of the AI/ML pipeline, including feature engineering, model selection, training, evaluation, and deployment strategies.
• Communicate complex analytical findings, insights, and recommendations clearly and persuasively to diverse audiences, including senior leadership and non-technical stakeholders, pitching Quickplay's data science capabilities and educating on data systems.
• Proactively identify business trends, opportunities, and problems through in-depth data analysis, ensuring continuous improvement of our data products and insights.
• Contribute to setting and executing the technical roadmap for the Data Science function, pushing for innovation and best practices.
• Mentor and provide technical guidance to junior data scientists, fostering their growth and ensuring analytical rigor in team projects.

Work Model:

Hybrid (3 days in office: Tuesday–Thursday; remote on Mondays and Fridays.)

Key Qualifications:

Cultural Fit:

At Quickplay, we thrive on a culture defined by four core principles. As a successful candidate, you'll demonstrate:

• Focusing on Impact: You are entrepreneurial, results-oriented, and proactive in addressing challenges. You prioritize solving needs and driving business impact through effective solutions.
• Being Curious: You actively seek to understand priorities, industry trends, and how Quickplay's solutions create value.
• Being Supportive: You foster collaboration across teams, build strong relationships, and ensure internal followership.
• Speaking Up: You offer constructive feedback when improvements are needed, driving continuous progress and accountability.

Technical Expertise and Background:

• 4+ years of progressive, applied experience in data science, machine learning, or advanced analytics roles, preferably within a software platform or OTT/media company.
• Senior individual contributor level.
• Extensive experience with machine learning on large, complex datasets, including model development, validation, and deployment in production environments.
• Deep expertise in statistical analysis, causal inference, experimental design (A/B testing), and a wide range of machine learning techniques.
• Advanced proficiency in Python or R for data manipulation, statistical modeling, and machine learning, along with expert-level SQL skills for data extraction and analysis.
• Proven experience with cloud-based data warehousing technologies such as BigQuery, Snowflake, or similar, and familiarity with distributed computing frameworks (e.g., Spark).
• Strong analytical and problem-solving skills, with a demonstrated ability to tackle highly complex and ambiguous business problems using scientific methods and data.
• Exceptional written and verbal communication skills, capable of translating intricate technical concepts into clear, concise, and strategic business recommendations for executive audiences.
• Self-starter with a strong sense of ownership, comfortable working autonomously and leading initiatives in a fast-paced, cross-functional environment.
• High emotional intelligence and low ego, enabling effective collaboration and mentorship.
• Quick learner with a deep understanding of technology opportunities and challenges at a business level.
• Experience interacting directly with customers and partners to gather requirements and present solutions.
• A graduate degree (Master's or Ph.D. preferred) in a quantitative field such as Data Science, Statistics, Computer Science, Machine Learning, Applied Mathematics, Economics, or a related discipline.
• Contribute to a fair, positive, and equitable environment that supports a diverse workforce.

Highly Favorable Skills:

• Experience with MLOps practices and tools for model versioning, monitoring, and automated retraining.
• Familiarity with the OTT video domain and technologies.
• Experience with business intelligence tools like Tableau or Looker for data visualization.
• Prior experience collaborating with academic institutions or leading internal research initiatives.
• Demonstrated experience in building and leading an expert data practice or analytics teams within a software platform company.