• Join the Tilt team • Help expand Tilt’s credit modeling and risk analytics capability for our Philippines-based business, Cashalo. • Build and refine underwriting models as well as other models, working at the intersection of credit, data science, and leadership. • Collaborate with a lean but growing team, applying advanced modeling techniques to predict loss performance, leverage alternative data sources, and build next-generation tools that shape credit access for millions. • Partner directly with cross-functional teams across credit, engineering, and leadership, bringing strong project and stakeholder management skills to a lean, fast-growing team.

Role Description We are seeking an experienced Product Owner with strong expertise in Snowflake or Databricks to oversee the delivery of an enterprise data lake initiative. This role combines product ownership, technical understanding, and data platform knowledge. The ideal candidate will collaborate closely with engineering, architecture, and business teams to convert requirements into actionable plans and drive the successful deployment of a scalable enterprise data platform. - Lead the end-to-end delivery of an enterprise data lake built on Snowflake or Databricks—from initial setup through production release - Translate business and data requirements into well-defined user stories, acceptance criteria, and sprint deliverables - Oversee the development of data ingestion and integration pipelines from SaaS platforms and other enterprise systems - Manage the full development lifecycle, ensuring timely completion of milestones and deliverables - Prioritize and maintain the product backlog based on business value, feasibility, and operational needs - Develop and manage a comprehensive delivery roadmap, including MVP releases and phased enhancements - Collaborate with cloud infrastructure and DevOps teams to ensure the platform is scalable, secure, and cost-efficient - Monitor and report key platform performance metrics such as pipeline success rates, processing times, and system reliability - Ensure a smooth transition to analytics and data science teams through proper documentation and operational readiness Qualifications - Proven experience as a Product Owner or Product Manager in data platforms, analytics, or cloud-based systems - Strong expertise in Snowflake or Databricks, including data modeling, data pipelines, and cloud architecture - Experience working with engineering, data, and DevOps teams in Agile/Scrum environments - Ability to translate complex business requirements into actionable technical plans - Familiarity with data ingestion, ETL/ELT workflows, and API-based integrations - Excellent communication and stakeholder management skills - Experience in HRMS or large-scale enterprise environments is a strong plus

Role Description 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 - Player decision systems Qualifications - Master’s degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Operations Research, Economics, or another related STEM field - 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 Requirements - 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 - 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 Company Description 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.

Role Description The Data Scientist is responsible for mining big data, interpreting and analyzing highly complex data sets from multiple sources using a variety of techniques to aid Mazda North American Operations in making smarter business decisions. The individual in this role utilizes expertise in data analysis, statistical modeling, and machine learning to unravel patterns, forecast trends, and uncover valuable information from diverse datasets to support business solutions. In this role, collaboration with stakeholders across the organization is essential to harness data and identify opportunities for leveraging company data to drive business solutions. The focus centers on wrangling large datasets from disparate sources, undertaking exploratory data analyses, identifying causal impact and attribution, and evaluating the effects of various campaigns. The development and application of data models and algorithms are critical to efficiently deploy new ideas as required by business teams. Major Areas of Responsibility - Data Science, Research & Analysis - 65% - Collects, preprocesses, and analyzes large datasets from various sources to extract meaningful insights and patterns. - Develops and deploys predictive models in order to analyze company performance, optimize maintenance schedules, and improve customer experiences. - Applies advanced statistical techniques and machine learning algorithms to identify correlations, anomalies, and trends within Mazda data. - Collaborates closely with data engineers, analysts, and business stakeholders to integrate data-driven solutions into our products and services. - Data Analytics Liaison - 20% - Advises organization on data science technologies and algorithms. - Advises and assists internal customers in resolving data-related issues while fostering data literacy. - Creates awareness of data products across the company. - Educates business partners on the critical nature of Data Science and how it provides value to their business, objectives, and goals; creates high-level data competency. - Serves as a SME for a specific area of data science for business partners. - Process Improvement - 15% - Remains up to date on industry standards, latest industry trends, best practices, and the evolving landscape of analytics. - Serves as a technical mentor to the data science team. Qualifications - Bachelor’s degree in Math, Statistics, Econometrics, Operations Research, Computer Science, Engineering or related field of study, or equivalent combination of education, training, and work experience. - Master’s in a quantitative discipline highly preferred. - Minimum of three (3) years hands-on work experience developing and applying predictive models and other advanced statistical approaches in a corporate or consulting setting. - Experience with visual analytics development and presentation. - Familiarity with data handling platforms (Hadoop, Spark, Hive, Power Pivot, Alteryx, SQL) and one or more data visualization packages (Tableau, Power BI). - Programming experience (Python, R, SQL). - At least one year of experience working with senior stakeholders and non-technical business leaders. - Prior work experience in marketing analytics preferred but not required. - Certifications and/or coursework in specific data science techniques and algorithms preferred. Requirements - Proven proficiency in statistical data analysis and data mining packages (e.g., R, NumPy, Pandas, TensorFlow, SciKit-Learn, SPSS, Alteryx, MatLab, STATA, Excel). - Working knowledge of data management tools including SQL/RDBMS, NoSQL (e.g., MongoDB), Hadoop and/or other big data technologies. - Advanced programming skills in at least one of Java, Python, R, C++, C#, etc. - Experience linking multiple data platforms with data visualization tools (e.g., PowerBI, Tableau). - Experience with marketing analytic models (attribution modeling, media mix models, etc.) preferred. - Knowledge of digital marketing analytics (Adobe, Google Analytics, Webtrends, DoubleClick, Atlas, etc.), and digital tag management. Direct experience with Adobe/Omniture a plus. - Intellectual curiosity, along with excellent problem-solving and quantitative skills. - Ability to communicate and present technical content in an easy-to-understand way. - Strong presentation skills. - Ability to produce timely deliverables and manage multiple and shifting priorities in a dynamic environment. - Proficiency with computer applications, including Microsoft Excel, Word, Project, PowerPoint and Outlook. - Well-balanced interpersonal skills; must be able to establish and maintain effective working relationships with all levels of management, employees, customers, and outside vendors. - Must be analytical and a problem solver with the ability to identify problems and/or cause-effect relationships. - Strong organizational skills and the ability to prioritize tasks are essential. - Self-motivated and capable of working with minimal supervision and/or direction. Travel - May be required 1 – 2 times per year. Pay Range $95,500.00 - $145,675.00. Salary to be determined by education, experience, knowledge, skills and abilities of the applicant, internal equity, and alignment with market data.