Data Scientist
Quickplay
Date: 1 week ago
City: Toronto, ON
Contract type: Full time
About us:
Quickplay fosters a transparent, fair, and collaborative environment where we enthusiastically tackle complex challenges in OTT video, emphasizing massive scale and resilience. Our high-performing, learning-oriented, and supportive culture makes us an ideal workplace for driven individuals.
As a Data Scientist at Quickplay, you will be a key member of our data science team, making substantial contributions to the development of new data-driven products and enhancing existing products that are serving our customers in production.
About the Role:
Key Responsibilities
Cultural Fit: Demonstrates mindset and behaviors such as:
Quickplay fosters a transparent, fair, and collaborative environment where we enthusiastically tackle complex challenges in OTT video, emphasizing massive scale and resilience. Our high-performing, learning-oriented, and supportive culture makes us an ideal workplace for driven individuals.
As a Data Scientist at Quickplay, you will be a key member of our data science team, making substantial contributions to the development of new data-driven products and enhancing existing products that are serving our customers in production.
About the Role:
Key Responsibilities
- Build Data Products: Partner with Product Management and Engineering teams to develop, launch and support innovative data products, such as recommendation systems and AI agents
- Support Data Science POCs: Support proof of concept initiatives to demonstrate AI-driven customer use cases.
- Developing AI/ML Pipelines:.Constructing and maintaining AI/ML pipelines, encompassing tasks such as feature extraction, model selection, and training.
- Data Extraction & Analysis: Apply various techniques, including statistical analysis and complex data mining, to interpret results and deliver meaningful insights.
- Client Communication: Communicate data-driven insights and suggestions to clients and potential clients with diverse technical backgrounds.
- Research & Development: Collaborate with academic institutions on research in strategic business areas and contribute to the Data Science technical roadmap.
- Hybrid: Work from home and office based on team needs.
Cultural Fit: Demonstrates mindset and behaviors such as:
- Focusing on Impact: Entrepreneurial, results-oriented, and proactive in addressing client challenges. You prioritize solving customer needs and driving business impact through effective solutions and positioning.
- Being Curious: Actively seeks to understand client priorities, industry trends, and how Quickplay’s solutions create value.
- Being Supportive: Fosters collaboration across teams, builds strong client relationships, and ensures internal followership.
- Speaking Up: Offers constructive feedback when improvements are needed, driving continuous progress and accountability.
- 3+ years of professional experience in an applied data science role, building data products.
- BS (or higher, e.g., MS or PhD) in Computer Science, Engineering, Mathematics, or Statistics.
- Familiarity with AI/ML techniques such as feature extraction, model selection, training, and deployment.
- Strong programming skills (Python, R, or similar)
- Experience with cloud computing (GCP and AWS)
- Proficiency with data manipulation and analysis tools (SQL, Pandas, NumPy)
- Strong written and verbal communication skills, with the ability to explain complex data concepts to both technical and business stakeholders. Proven ability to collaborate across cross-functional teams and contribute to achieving business goals.
- Strong problem-solving skills, with a desire to both learn and teach others. Self-motivated with the ability to work autonomously and in teams.
- Solid understanding of data products, data visualization, analytics, statistics, and machine learning. A passion for continuously improving technical expertise.
- Contributing to advanced technical projects and business issues requiring foundational data science knowledge.
- Assisting in developing strategies, setting clear objectives, and contributing to the growth of the data science function.
- Collaborating with Engineering and Product teams to achieve shared business and product goals.
- Supporting the team in delivering data-driven approaches influencing product decisions and business outcomes.
- Continuously learning and staying up-to-date with machine learning techniques and methodologies to improve work efficiency and impact.
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