The custodian of the AI and Data Science craft across X, bigly labs, spanning Data Science, Machine Learning, AI Engineering and MLOps/ LLMOps. The role independently leads day-to-day technical direction, craft operations and delivery assurance across tribes and domains.
Responsibilities
Define and maintain standards for data science, AI engineering, ML/LLM lifecycle, experimentation, documentation, version control, and deployment
Maintain role profiles, competency frameworks and technical expectations for Data Scientists, AI Engineers and ML/MLOps practitioners
Set quality gates for data suitability, model validation, bias and robustness checks, LLM evaluation, security, deployment readiness, and post-release monitoring
Establish reproducible development and deployment practices, model/experiment tracking, registries, release controls, and monitoring with platform teams
Establish and run AI and Data Science communities of practice with charters, roadmaps, and practical knowledge-sharing
Explore business challenges, develop hypotheses, choose suitable analytical methods, and deliver data-driven solutions
Develop, test, and improve predictive algorithms and artificial intelligence techniques to improve player experiences, engagement, retention, and revenue
Apply statistical analysis, forecasting, predictive modelling, and simulation to understand player behaviour and business performance
Support A/B testing and experiments by selecting relevant metrics, analysing results, and sharing findings that guide business decisions
Create analytical models, simulations, and tools that help teams make informed decisions and find opportunities for improvement
Requirements
MSc or PhD in Data Science, Computer Science, Statistics, Physics, Mathematics, or a related quantitative field, or possessing equivalent experience
Develops, implements, and optimizes credit risk decision-making strategies for personal financing products using machine learning and predictive modelling.
Compensation
Competitive salary and annual bonus
Responsibilities
Optimize and develop decision-making strategies for credit management and prepare associated documentation
Apply your knowledge of machine learning and predictive modelling to maximize financial impact and support credit risk strategies
Participate in complex data analyses (SAS, Python), interpret results, build replicators and monitor how our strategies perform once in production
Monitor financing products and conduct quarterly performance reviews
Contribute to various projects, assignments and data analyses in your area of expertise and make recommendations aligned with strategic priorities
As a Senior Demand Forecast Analyst – NAM, you will sit at the intersection of data science and commercial planning, building and improving the statistical forecasting models that underpin demand planning capability.
Compensation
The salary range for the role is CAD$94,000 - CAD$124,000
Responsibilities
Developing and maintaining statistical forecasting models, enhancing baseline forecast generation, and evaluating and implementing new forecasting techniques
Improving forecast accuracy by identifying patterns, trends, and demand drivers, and continuously evolving modelling approaches to strengthen the demand signal
Driving automation and process improvement to reduce manual overrides, and reporting on visualizing data to communicate findings to planning and commercial partners
Partnering with demand planning teams to improve forecast adoption, balancing model output with business context to ensure forecasts are both technically sound and commercially relevant
Translating complex analytical outputs into clear, actionable insights for non-technical stakeholders across planning, merchandising, and commercial functions
Lead cross‑cutting data and BI initiatives across multiple domains, establishing governance, standards, and portfolio management without direct people‑management responsibility.
Compensation
The pay range for this position is as follows:
117,100.00--156,200.00
Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate. This position is also eligible for participation in a performance-based bonus plan.
Responsibilities
Owns portfolio governance across multiple Data & BI Operations products and domains
Frames complex business and technical problems
Creates and institutionalizes discovery, requirements, prioritization, delivery, governance, documentation, and intake standards
Lead and contribute to the delivery of client projects and engagements, ensuring high-quality outputs and actionable insights and recommendations that align with client objectives.
Compensation
Salary range $70,000 - $85,000
Responsibilities
Lead and contribute to the delivery of client projects and engagements
Collaborate with senior marketing executives and other stakeholders to identify business challenges and opportunities
Develop and implement analytical frameworks, measurement strategies, and reporting solutions
Assist in executing the strategic vision for the CCA consulting practice
Analytical partner to Springer Nature's China Marketing team, combining analytics, consultancy, and stakeholder collaboration to drive better business outcomes.
Responsibilities
Partner with local marketing stakeholders to adapt and extend the marketing KPI and metrics framework
Partner with local marketing stakeholders and the wider Marketing Optimisation & Impact team to shape measurement approaches
Manage and analyse large and complex datasets from multiple sources using SQL and Python or R on cloud-based data platforms
Apply statistical methods, modelling techniques, and strong quantitative skills to support marketing optimisation and impact measurement
Support experimental design and advise on the interpretation of test results and experimentation best practices
Requirements
Nice to have: dbt
Nice to have: Modern analytics engineering practices
Nice to have: Chinese academic and research landscape
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