Staff Data Scientist

Les Produits Scientific Games Canada; Toronto; Hybrid; CAD 140,000 - 200,000; Full time

Job summary

Scientific Games is seeking a founding Staff Data Scientist to build the decision science function from the ground up in Canada. You will define modeling standards, roadmaps, and productionization of high-impact DS systems spanning forecasting, personalization, and pricing.

The role starts remotely and moves to a hybrid setup once possible; candidates must be local to Toronto, ON, to collaborate with the founding team and scale the DS platform across the organization.

Qualifications

• Master's degree or PhD in CS, Stats, Math, Eng, OR/ Economics or related STEM field.
• 6+ years post-Master's or 4+ years post-PhD in data science or applied ML.
• Proven leadership of high-impact DS initiatives from framing to production.
• Experience in forecasting, optimization, experimentation, or recommendation systems.
• Strong Python (pandas, scikit-learn, PyTorch, TensorFlow) and SQL skills.
• Experience mentoring DS teams and shaping technical standards.

Responsibilities

• Lead design and delivery of high-impact decision science systems across forecasting, optimization, experimentation, and real-time recommendations.
• Translate opportunities into structured modeling roadmaps, milestones, and KPI frameworks.
• Partner with Principal DS to set modeling standards, guardrails, validation, and deployment playbooks.
• Build production-grade decision engines for personalization, pricing, and portfolio optimization.
• Design multi-stage ranking architectures (retrieval to re-ranking).
• Mentor DS engineers and raise technical rigor in statistics, causal inference, and experimentation.
• Shape reusable DS workflows integrated with the self-service ML platform.

Skills

Forecasting

Optimization

Experimentation

Recommendation systems

Pricing

Portfolio science

Causal inference

Python

SQL

Leadership

Education

Master's degree or PhD in CS/Statistics/Math/Engineering/OR/Economics or related STEM

Tools

Databricks

PySpark

MLflow

Cloud deployment workflows

Job description

Scientific Games: Scientific Games is the global leader in lottery games, sports betting and technology, and the partner of choice for government lotteries. From cutting-edge backend systems to exciting entertainment experiences and trailblazing retail and digital solutions, we elevate play every day. We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation, legendary performance, and unwavering security to responsibly propel the global lottery industry ever forward.

Position Summary About the Role

We are looking for a founding Staff Data Scientist to help build the decision science function from the ground up and translate our long-term product and decisioning vision into scalable production systems. This is not a maintenance role. As an early senior technical leader, you will work closely with the Principal Data Scientist, Staff peers, and Senior Data Scientists to define the modeling standards, decision science patterns, and execution playbooks that will become the backbone of the organization. This role sits at the intersection of technical depth, platform leverage, and strategic execution. Despite being part of a large organization, the team operates with a startup mindset: fast-paced, highly iterative, and biased toward rapid execution, learning, and measurable business impact. You will own some of the organization’s highest-value problems across forecasting, experimentation, personalization, recommendation systems, portfolio optimization, pricing, and player decision systems.

This position will start remotely and transition to a hybrid role. Candidates must be local to Toronto, ON.

Key Responsibilities

• Lead the design and delivery of high-impact decision science systems across forecasting, constrained optimization, experimentation, and batch and real-time recommendation systems
• Translate ambiguous business opportunities into structured modeling roadmaps, milestones, and measurable KPI frameworks
• Partner with the Principal Data Scientist to establish modeling standards, experimentation guardrails, validation frameworks, and deployment playbooks for the founding DS organization
• Build production-grade decision engines spanning player personalization, next-best-action systems, pricing, portfolio optimization, and retail recommendation use cases
• Drive the design of multi-stage recommendation and ranking architectures, including retrieval, pre-ranking, ranking, and re-ranking
• Mentor Senior and mid-level Data Scientists while raising technical rigor across statistical thinking, causal inference, optimization, and experimentation
• Shape the evolution of reusable DS workflows that integrate cleanly with the self-service ML platform being built by the founding MLE team

Required Qualifications

• Education: Master's degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Operations Research, Economics, or another related STEM field
• Experience: 6+ years post-Master's experience or 4+ years post-PhD experience in data science, decision science, econometrics, or applied machine learning
• Proven experience leading ambiguous, high-impact data science initiatives from framing through production business impact
• Strong experience in at least three of: forecasting, optimization, experimentation, recommendation systems, pricing, portfolio science, or causal inference
• Experience mentoring Data Scientists and shaping technical standards beyond individual project delivery
• Technical Skills: Strong Python proficiency across pandas, scikit-learn, PyTorch, and TensorFlow
• Deep expertise in statistical modeling, experimentation, causal inference, and optimization
• Strong SQL and large-scale data experience
• Hands-on experience building batch and real-time recommendation or decision systems
• Familiarity with multi-stage cascading ranking architectures and decision APIs
• Leadership: Ability to translate long-term product vision into executable decision science roadmaps
• Strong technical mentorship and review discipline
• Ability to influence DS standards, experimentation culture, and KPI rigor across the founding team

Preferred Qualifications

• Experience as a founding or early senior hire in a new DS organization
• Hands-on portfolio optimization, payout optimization, assortment optimization, or mathematical programming
• Experience with personalization, gaming, retail, marketplace, or digital consumer decision systems
• Experience working with self-service experimentation and ML platforms
• Familiarity with Databricks, PySpark, MLflow, and cloud-native deployment workflows
• Strong product intuition for balancing revenue, margin, player engagement, and responsible gaming constraints

SG is an Equal Opportunity Employer and does not discriminate against applicants due to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

If you'd like more information about your equal employment opportunity rights as an applicant under the law, please click here for EEOC Poster.

Relentless innovation. Legendary performance. And unwavering security. All built on a foundation of trusted partnerships. This is what it takes to be a global leader in lottery games, sports betting and technology. And to propel the industry ever forward. At Scientific Games, we elevate play every day. From cutting-edge backend systems to exciting entertainment experiences and trailblazing retail and digital solutions, we care about the details that drive profits for lottery beneficiary programs. We know what people like to play today. And with the power of data analytics, we can predict what they'll want to play tomorrow. We're always thinking about the player experience. Because it's not just a game. It's an instant of optimistic fun. But the best part? We're just getting started. iLottery and sports betting are the new frontier in play. And Scientific Games is the partner of choice for these growing markets. Because when it comes to digital, trust is everything. The lottery experience is always one of excitement. But we're endlessly innovating, always evolving and firmly committed to responsible gaming. So that the future of lottery funding shines bright. It's a future of stability and inspiration. The strength of security paired with the thrill of the new. It's the future of Scientific Games. The driver of today's favorite lottery games and most advanced technologies, and sustainability for tomorrow. And it all starts now.