Data Scientist

• Build and maintain new data models that are accurate and reliable
• Work closely with a wide range of stakeholders from Data Science, Commercial Leadership, Sales Operations, Product, Design, and Engineering
• Define, prototype, implement and improve ML models
• Design experiments to test hypotheses (e.g. which customers should we focus on in our outbound calls)
• Build/maintain reports, dashboards, and metrics to support our north star metrics
• Teach and learn from their teammates. We value making others successful

Senior Data Scientist, Sales

• You serve as a methodological thought partner to study teams, providing expert guidance on complex design and analysis across programs
• You lead the development and institutionalization of methodologies that improve decision-making at trial and portfolio levels (e.g., quantitative go/no-go criteria, simulation frameworks, model-based projections)
• You shape cross-functional understanding of innovative statistical methods through consultation, publications, and leadership of education efforts
• You anticipate regulatory trends and industry shifts, integrating relevant methodologies into internal practices and guiding external engagements
• You act as a connector across teams, surfacing recurring challenges and co-creating scalable solutions to elevate analytical excellence in the organization
• You drive external collaboration through active participation in consortia, joint working groups, or regulatory-facing initiatives
• You mentor junior staff and influence the strategic direction of Statistical Methodology through thought leadership, vision-setting, and capability building.

Principal Data Scientist – Statistical Methodology

• Collect, clean, and transform large, complex datasets for analysis
• Build custom machine learning models and natural language processing systems
• Leverage tools like TensorFlow, PyTorch, Kubernetes, and Nvidia Triton Servers
• Train, evaluate, and optimize models for accuracy, explainability, and ethical alignment
• Clearly communicate technical analysis and results to stakeholders
• Continuously monitor models and data pipelines in production
• Stay up to date on the latest advancements in deep learning, NLP, reinforcement learning, and other AI methods.

Senior Data Scientist, ASR

• Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment
• Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
• Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches
• Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product teams can measure true causal impact rather than biased local estimates
• Identify opportunities where improved experimentation methodology can unlock product insights that were previously unmeasurable or ambiguous
• Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
• Influence the long-term product strategy by driving learning through well-designed experiments and translating experimental results into clear, actionable recommendations for senior leadership
• Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor
• Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader experimentation and causal inference community

Senior Staff Data Scientist – Consumer Experimentation

• Serve as the technical authority on relevance metrics and evaluation methodology across Consumer, setting standards for how we measure the quality of feeds, search results, and recommendations in a complex, community-driven environment
• Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems, including proxy metrics that reliably predict long-term outcomes like retention, community health, and user satisfaction
• Design and analyze experiments for relevance features, accounting for challenges unique to networked platforms such as spillover effects between communities, interference between contributors and consumers, and long-run impacts of ranking changes on content supply
• Identify opportunities where improved measurement and analysis can unlock product insights that were previously unmeasurable or ambiguous, particularly around content quality, search intent understanding, and personalization effectiveness
• Partner deeply with ML engineers and product teams to translate model performance metrics into user-facing impact
• Influence the long-term product strategy for Feeds and Search by synthesizing insights from experimentation, observational analysis, and metric deep-dives into clear, actionable recommendations for senior leadership
• Mentor and elevate other data scientists across the organization on relevance evaluation, experimentation best practices for ranking systems, causal reasoning, and statistical rigor
• Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader relevance, recommendation systems, and experimentation community

Senior Staff Data Scientist – Consumer Relevance

• Develop predictive modeling and machine learning solutions to complex business problems creating value for the business.
• Transform data into insights that help to improve the value of the business.
• Execute exploratory data analysis, data preprocessing, model development, model deployment and monitoring.
• Utilize machine learning techniques to improve customer segmentation, churn prediction, and personalized marketing efforts.
• Plan and execute analytical experiments to help solve business problems.
• Propose solutions and strategies to business challenges.
• Continuously refine and improve models based on feedback and changing business needs.
• Leverage advanced analytics techniques to develop deep knowledge of the customer experience, use data and analytics to optimize marketing campaigns, and develop strategies through insights to attract new customers and retain existing ones.
• Collaborate with business partners to develop novel ways to meet objectives utilizing cutting edge techniques and tools.
• Effectively communicate the analytics approach and data science lifecycle with leadership and business partners.
• Advocate and educate on the value of data driven decision making focusing on the “how and why” of solving problems.
• Lead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts and developers.
• Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products.
• Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources.
• Build and deploy agentic AI solutions that leverage autonomous reasoning and tool-calling to automate end-to-end workflows and improve decision-making efficiency.
• Share your passion for Data Science with broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.
• Collaborate, coach, and learn with a growing team of experienced Data Scientists.

• Ensure that modelling processes make appropriate use of available data based on characterization, quality and processing as part of strategic initiatives
• Ensure that predictive modelling is carried out according to the required standards and that Desjardins Group’s quality criteria are met through the validation process
• Analyze the business needs behind the model and confirm the model’s suitability through validation
• Ensure that the programming required to prepare and mine data, and to develop, evaluate, support, roll out and manage highly conceptually complex and innovative models meets the required standards
• Use advanced and innovative statistical, machine learning and artificial intelligence methods to test the methodologies proposed by the first line of defence
• Help draft guidelines and methods and shape methodological and technological choices
• Advise and train teams on quantitative model validation methods and update them to improve delivery speed
• Identify opportunities to optimize rules and systems, anticipate underlying impacts of changes and help develop data management and modelling support tools
• Represent teams with various internal interested parties
• Monitor the industry to understand and anticipate trends in your field of expertise in model validation, with a view to developing and updating practices that are contextually appropriate for the organization
• Ensure alignment with relevant regulatory expectations for property and casualty (P&C) insurance

Data Scientist, Model Validation

• You don’t just work with data—you decode it, predict the future with it, and turn it into action.
• Your models don’t just sit on a shelf—they shape strategy, optimize efficiency, and fuel company growth.
• You thrive on uncovering hidden patterns, validating hypotheses, and embedding machine learning models into real-world AI applications.

Associate Data Scientist

• Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.
• We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space.
• We are looking for a Senior Data Scientist with a good blend of data analytics background, practical experience in Operation research strategies and Pricing Analytics within supply chains, and strong coding capabilities to add to our team.
• **Key Responsibilities:**
• - Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming
• - Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG.
• - Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization.
• - Develop and implement predictive models and optimization algorithms to improve Pricing techniques.
• - Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
• - Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization.
• - Collaborate, coach, and learn with a growing team of experienced Data Scientists.

Senior Data Scientist – Operation Research

• Building Reinforcement Learning models to solve business problems in a production environment.
• Drive significant incremental business value by leveraging advanced machine learning to design, test, and implement advanced data science approaches for dynamic pricing, real-time offer allocation, and personalization, improving targeting and offer assignment within our marketing engine.
• Develop and optimize algorithms that balance business constraints, customer behavior, and engagement objectives to deliver optimal, data-driven decisions across offers and pricing.
• Design, enhance, and generalize models into scalable solutions that can be applied across products, partners, and diverse data environments.
• Leverage a wide range of data sources (e.g., partner, product, and third-party data) to enrich algorithms and clearly demonstrate measurable business impact.
• Lead and collaborate with cross-functional teams (Product, Engineering, Analytics) to establish best practices for developing, automating, and standardizing advanced data science solutions, with an emphasis on real-time applications.
• Champion scalable, automated production deployments by integrating algorithms into live systems through rapid iteration and experimentation, leveraging AWS infrastructure (particularly SageMaker) to deploy, monitor, and scale models in production.

Senior Data Scientist – Reinforcement Learning

• Own marketing tests end-to-end, leveraging and contributing to our Python-based measurement workflows.
• Collaborate with senior ICs to address critical data infrastructure needs, support org-wide migrations, and develop new analytical and measurement solutions.
• Develop reporting and monitoring tools that surface business insights and increase visibility into marketing performance and impact.
• Conduct deep-dive analyses to investigate questions related to performance, audiences, monetization, attribution, and data integrity.
• Provide flexible analytical support across the team’s project portfolio, taking high-level direction from senior ICs while independently owning specific components of the solution.

Senior Marketing Data Scientist

• Help draft and update methodological documentation for derivatives and market risk models
• Help update and document quantification methodologies for risk metrics (VaR, stress tests) and regulatory frameworks (FRTB, SIMM, ICAAP), according to the established standards
• Help review model inputs and components, in collaboration with stakeholders
• Help implement new products in risk systems (Murex, MSCI RiskMetrics, FIS Adaptiv)
• Participate in workshops to formalize model needs and support their implementation
• Contribute to the development of risk modelling practices through analysis, proposals and exploratory work

Data Scientist, Market Risk Model Design

• Engage with all levels of the TD Auto Finance team and utilize skills to provide value added information to business stakeholders
• Work with business partners on initiatives and projects
• Provide consultation and recommendations by highlighting impacts from a quantitative point of view
• Pro-actively identify opportunities for the business to maximize shareholder value through provisioning of analytics discovery and business insights
• Support a positive work environment that promotes service to the business, quality, innovation, and teamwork
• Manage, update, and maintain financial models and profitability reports for consumption of product partners
• Provide ad hoc support to Senior Manager in strategic and tactical initiatives as required

Data Scientist III

• Refactor Neural Network Collaborate with architect and author of neural network bond risk product to identify areas for improvement.
• Lead architecture and development effort Ongoing Contribute to the design, development, and deployment of firm-wide architecture, norms, policies, infrastructure and methodologies for machine learning activities across multiple company groups.
• Design, develop, and deploy machine learning models into production environments.
• Collaborate with data scientists to translate prototypes into production-ready systems.
• Build and maintain data pipelines, feature stores, and model-serving infrastructure.
• Evaluate and optimize model performance, latency, and scalability.
• Implement automated training, testing, and deployment workflows (MLOps).
• Monitor models in production and address issues related to drift, performance degradation, or data quality.
• Conduct code reviews and ensure best practices in ML engineering and software development.
• Stay current with emerging ML/AI technologies and recommend tools or frameworks that improve team efficiency.

Data Scientist / ML Engineer

• Be responsible for the quality and statistical research rigor of Numeris data products including developing and reviewing weighting, fusion, calibration, attribution and other statistical processes as well as the accuracy and reliability of data outputs.
• Manage the Data Science team in order to provide recommendations for the use of statistical, Data Science and AI methodologies, the continuous improvement of current analytical data processes and procedures, and the expansion of value added to data products.
• Oversee the application and review of data mining, data integration and hybrid methodologies. Assess the integrity of statistical and machine learning models developed internally or built externally by business partners, guaranteeing the use of rigorous research statistical and data science standards.
• Develop and support alternative or new approaches including hybrid methodologies for the mining, management, production and usability of new data outputs, leveraging both data and information from a variety of internal and external sources.
• Produce, supervise and vet reports and recommendations based on data modelling, advanced analytics and simulations with business impact on Numeris clients.
• Support automation projects throughout the organization by implementing solutions that drive efficiency.
• Work closely with Data Science partners, as well as internal Product, Technology and Operations staff.

Senior Manager, Data Science

• Design, develop, validate, and improve data science models and products
• Participate in stakeholder planning sessions to recommend data science modeling approaches
• Use SQL to transform complex data and build scalable datasets
• Collaborate with product owners to shape new data product ideas

Senior Data Scientist

• Lead the development, validation, productionization, and iteration of machine learning models that support city and vehicle tech initiatives, including feature engineering, model selection, performance tuning, and integration into product and enforcement systems
• Define and establish model and product performance metrics, building clear evaluation frameworks to assess live performance and guide data-driven decision-making
• Own and contribute to the development of analytical data pipelines and instrumentation required to support modeling, experimentation, and reliable reporting
• Design, lead, and support experimentation efforts, including product initiatives and pilot programs, to measure impact, validate performance, and deliver insights that inform broader product and business strategy
• Manage complex, cross-functional initiatives from scoping through executive communication
• Make business recommendations using effective presentation skills, conveying findings at multiple levels including executive leadership, managers, and peers

Senior Data Scientist, City and Vehicle Tech

• Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.
• Leading the development of advanced AI and machine learning models to solve complex business problems
• Research, build, and deploy models based on both shallow and deep machine learning.
• Train robust NLP-based models on a very large corpus of data
• Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.
• Mentoring junior data scientists and provide guidance on AI and machine learning best practices.
• Designing APIs for disseminating data science outputs to various business units.
• Overseeing the scaling of production systems to meet growing demands.

Senior Data Scientist – French Language Proficiency

• Develop and evolve statistical and causal inference methodologies that strengthen the rigor and reliability of Northbeam’s marketing measurement products
• Enhance the accuracy, robustness, and scalability of existing MMM pipelines
• Write production-quality Python and SQL, collaborating closely with Engineering to integrate statistical workflows into scalable systems
• Rigorously assess model assumptions, identify potential sources of bias, and implement mitigation strategies
• Debug data and modeling issues in production and improve the reliability of customer-facing results
• Translate complex statistical reasoning into clear, decision-ready insights for internal stakeholders and customers

Staff Data Scientist

• Contribute to development and maintenance of Machine Learning models for business problems.
• Contribute to model evaluation, parameter tuning, feature selection and model calibration experiments for predictive analytics projects.
• Contribute towards prompt engineering for data analysis and discovery.
• Conduct regular testing and performance analysis.
• Conduct necessary bench-marking experiments.

See all jobs on JobTailor

Senior Data Scientist, Sales

Principal Data Scientist – Statistical Methodology

Senior Data Scientist, ASR

Senior Staff Data Scientist – Consumer Experimentation

Senior Staff Data Scientist – Consumer Relevance

Data Scientist

Data Scientist, Model Validation

Associate Data Scientist

Senior Data Scientist – Operation Research

Senior Data Scientist – Reinforcement Learning

Senior Marketing Data Scientist

Data Scientist, Market Risk Model Design

Data Scientist III

Data Scientist / ML Engineer

Senior Manager, Data Science

Senior Data Scientist

Senior Data Scientist, City and Vehicle Tech

Senior Data Scientist – French Language Proficiency

Staff Data Scientist

Data Scientist