Staff Data Scientist

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.

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 organizations 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 thinkingcausal 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:

• Masters degree or PhD in Computer Science Statistics Mathematics Engineering Operations Research Economics or another related STEM field

Experience:

• 6 years post-Masters 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 youd like more information about your equal employment opportunity rights as an applicant under the law please click here for EEOC Poster.