Staff Data Scientist

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.

Qualifications

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 role is based out of Toronto.

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