Analytical Scientist jobs

Being the cybersecurity partner of choice, protecting our digital way of life.

Your Career

As a Staff AI Scientist for Enterprise AI Solutions, you will be a critical technical leader responsible for the hands-on design, development, and implementation of AI-powered solutions that solve challenging business problems across IT and various enterprise functions (Sales, Marketing, Finance, HR, Legal, etc.). You will work closely with Principal and Distinguished Architects to translate high-level strategies into concrete AI solution designs and robust, scalable, and ethical implementations. This role demands deep technical expertise, a strong ability to solve complex problems, and a commitment to mentoring other engineers, leveraging our Enterprise AI Platform to deliver measurable business impact

Your Impact

• AI Solution Implementation: Lead the design and implementation of AI solutions, translating business problems into AI designs, and managing model selection, data requirements, and integration for AI applications.
• Platform Development: Develop and implement core components of the enterprise AI/ML platform, ensuring scalability and security. Contribute to the lifecycle of traditional and Generative AI model deployment and real-time inference systems.
• System Optimization: Design and optimize large-scale AI/ML systems for performance, reliability, and developer-friendliness, focusing on low latency and high throughput in real-time AI applications.
• Technology Adoption: Evaluate and integrate new AI tools, frameworks, and cloud solutions, aligning with architectural guidelines. Lead POCs for emerging AI innovations.
• Architectural Best Practices: Champion design standards and best practices for AI systems, guiding junior engineers.
• Technical Leadership: Mentor AI/ML engineers, lead design discussions, and perform code reviews, fostering engineering excellence.
• Cross-Functional Collaboration: Partner with Data Scientists, ML Engineers, Product Managers, and IT stakeholders to develop production-grade AI solutions.
• Responsible AI & Quality: Ensure AI systems comply with responsible AI principles and security policies. Implement automated testing and monitoring.
• Innovation & Research: Apply cutting-edge AI/ML techniques to solve problems and improve solutions, staying updated on advancements in Generative AI and LLMs.

Your Experience

• 8+ years in software engineering, with 5+ years in Data science/AI/ML experience.

• Experience deploying enterprise AI/ML systems.

• Understanding of the AI lifecycle.

• Experience with distributed systems and streaming data.

• Hands-on experience with Generative AI and LLMs.

• Proficiency in AI/ML frameworks and cloud platforms.

• Strong programming skills (Python and C++).

• Excellent communication skills.

• Masters/Bachelors degree in Computer Science or related field.

Preferred Qualifications:

• PhD degree in Computer Science , Applied Mathematics , Machine Learning or related computation field.

• Experience with open-source AI projects.

• Prior technical lead role for AI/ML projects.

• Familiarity with cybersecurity principles for AI.

What we are looking for?

• Deep Technical Expertise: Strong foundation in machine learning (theory and application), deep learning, statistical modeling, and relevant programming languages (Python, R) and libraries (TensorFlow, PyTorch, scikit-learn).

• Proven Research & Innovation: Track record of conceiving and executing novel research, publishing in top-tier conferences/journals, or delivering innovative AI solutions with significant business impact.

• System Design & Scalability: Ability to design, build, and deploy scalable and robust AI systems. Understanding of MLOps and data engineering principles.

• Problem Solving & Critical Thinking: Excellent analytical skills to tackle complex, ambiguous problems and break them down into manageable parts.

• Leadership & Mentorship: Experience in leading projects, guiding junior team members, and influencing technical direction.

• Communication & Collaboration: Ability to clearly communicate complex technical concepts to diverse audiences (technical and non-technical) and collaborate effectively with cross-functional teams.

• Business Acumen & Impact Focus: Understanding of how AI can drive business value and ability to translate research/technical work into tangible outcomes.

• Continuous Learning: Passion for staying up-to-date with the latest advancements in AI.

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $165,000 - $250,000/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found .

All your information will be kept confidential according to EEO guidelines.

The Community You Will Join:

You will join a team dedicated to driving innovation and optimizing our dynamic Marketplace. As a member of the Marketplace Data Science team, you will tackle challenges at the core of our business, including pricing, supply management, and fee strategies. Collaborating with leaders across the company, you will play a key role in shaping the future of our marketplace.

The Difference You Will Make:

As a Staff Data Scientist, you will be responsible for building data products, inference frameworks, and intelligence to enable the growth of our marketplace. Your work will include:

• Specifying and estimating models to determine the impact of supply and demand on marketplace outcomes
• Delivering data and insights to enable the company’s supply growth efforts
• Providing mentorship to other data scientists and exemplifying a high bar for technical excellence

A Typical Day:

• Crafting models: You will develop models to accurately forecast key marketplace metrics, enabling proactive decision-making and strategic planning.
• Advanced causal inference: Utilizing cutting-edge causal inference techniques, you will quantify the impact of changes in supply and demand on the marketplace, informing targeted improvements and interventions.
• Cross-functional collaboration: You will actively collaborate with teams across product, engineering, and operations to integrate data science insights into initiatives aimed at enhancing supply acquisition, retention, and success.
• Stakeholder engagement: You will engage with stakeholders to understand their business objectives and provide data-driven solutions tailored to these goals.

Your Expertise:

• 9+ years of relevant industry experience and a Master’s degree or PhD in a quantitative field
• Strong fluency in Python or R for hands-on IC work and SQL for advanced data analysis at scale
• Experience with causal inference and machine learning techniques, ideally in a multi-sided platform setting
• Proven ability to succeed in collaborative environments with cross-functional stakeholders and also in independent work environments
• Proven ability to communicate clearly and effectively to audiences of varying technical levels

Offices: United States

Being the cybersecurity partner of choice, protecting our digital way of life.

Your Career

You will be constantly challenged by tough engineering and design tasks, working in a fast-paced setting to deliver high-quality, impactful work.

Your Impact

In this versatile role, you will drive impact across both data engineering and data science domains:

Data Engineering Foundations

• Design & Development: Design and implement scalable data architectures and datasets that support the organization's evolving data needs, providing the technical foundations for our analytics team and business users.

• Data Engineering: Support and implement large datasets in batch/real-time analytical solutions leveraging data transformation technologies.

• Data Security & Scalability: Enable robust data-level security features and build scalable solutions to support dynamic cloud environments, including financial considerations.

• Process Improvement: Perform code reviews with peers and make recommendations on how to improve our end-to-end development processes.

AI/ML Innovation & Business Impact

• Develop & Deploy Classical ML Models: Own the end-to-end lifecycle of machine learning projects. You'll build and productionize sophisticated models for critical business areas such as marketing attribution, customer churn prediction, case escalation and other relevant use-cases to post-sales.

• Optimize AI Agentic Systems: Play a key role in our generative AI initiatives. You will be responsible for characterizing, evaluating, and fine-tuning AI agents—such as conversational systems that allow users to query massive datasets using natural language—to improve their accuracy, efficiency, and reliability.

• Partner with Business Stakeholders: Act as an internal consultant to our Go-to-Market (GTM), Global Customer Services (GCS) and Product and Finance teams. You'll translate business challenges into data science use-cases, identify opportunities for AI-driven solutions, and present your findings in a clear, actionable manner.

• Own the Full Data Science Lifecycle: Your responsibilities will cover the entire project workflow, working with the business to understand the problem, charting a path to solve the problem, feature engineering, model selection and training, robust evaluation, deployment, and, in partnership with the data platform team, ongoing monitoring for performance degradation.

Your Experience

• 7 plus years experience building and maintain data pipeline both for reporting, analysis and feature engineering.

• Experience building and optimizing clean, well-structured analytical datasets for business and data science use cases. This includes Implementing and supporting Big Data solutions for both batch (scheduled) and real-time (streaming) analytics.

• Prior experience working extensively within dynamic cloud environments, specifically Google Cloud Services (GCS) BigQuery and Vertex AI.

• Prior experience developing dashboards in Tableau/Looker or similar data viz platform.

• Nice to have: Experience implementing and managing data-level security features to ensure data is protected and access is properly controlled.

• Expert-level programming skills in Python and familiarity with core data science and machine learning libraries (e.g., Scikit-learn, Pandas, PyTorch/TensorFlow, XGBoost).

• A solid command of SQL for complex querying and data manipulation.

• Proven ability to work autonomously, navigate ambiguity, and drive projects from concept to completion.

Preferred Qualifications

• Prior working experience in Customer Analytics space and customer experience use-cases, e.g. Escalation, Risk predictors, Renewals and efficiency of project delivery in Professional Services space.

• Direct experience with generative AI, including hands-on work with LLMs and frameworks like LangChain, LlamaIndex, or the Hugging Face ecosystem.

• Experience in evaluating and optimizing the performance of AI systems or agents.

• Demonstrated expertise in specialized modeling domains such as causal inference, time-series analysis.

• An MS or PhD in a quantitative field like Computer Science, AI, Statistics, or equivalent practical experience or equivalent military experience.

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $143000- $231000/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found .

All your information will be kept confidential according to EEO guidelines.

The Community You Will Join:

You will join a team dedicated to driving innovation and optimizing our dynamic Marketplace. As a member of the Marketplace Data Science team, you will tackle challenges at the core of our business, including pricing, supply management, and fee strategies. Collaborating with leaders across the company, you will play a key role in shaping the future of our marketplace.

The Difference You Will Make:

As a Senior Data Scientist, you will be responsible for building data products, inference frameworks, and intelligence to enable the growth of our marketplace. Your work will include:

• Specifying and estimating models to determine the impact of supply and demand on marketplace outcomes
• Delivering data and insights to enable the company’s supply growth efforts

A Typical Day:

• Crafting models: You will develop models to accurately forecast key marketplace metrics, enabling proactive decision-making and strategic planning.
• Advanced causal inference: Utilizing cutting-edge causal inference techniques, you will quantify the impact of changes in supply and demand on the marketplace, informing targeted improvements and interventions.
• Cross-functional collaboration: You will actively collaborate with teams across product, engineering, and operations to integrate data science insights into initiatives aimed at enhancing supply acquisition, retention, and success.
• Stakeholder engagement: You will engage with stakeholders to understand their business objectives and provide data-driven solutions tailored to these goals.

Your Expertise:

• 5+ years of relevant industry experience, or 2+ years with a PhD
• Background in economics, statistics, and experimentation. A PhD or Master’s in economics or a related field is valued
• Strong fluency in Python or R for hands-on IC work and SQL for advanced data analysis at scale
• Experience with causal inference and machine learning techniques, ideally in a multi-sided platform setting
• Proven ability to succeed in collaborative environments with cross-functional stakeholders and also in independent work environments
• Proven ability to communicate clearly and effectively to audiences of varying technical levels

Offices: United States

A Typical Day:

• Inference: Develop and apply causal inference methods, including experimental, econometric regressions, and quasi-experimental methods to measure a wide-range of platform/product impacts.
• AI/ML: Build methods for robust evaluation of ML/AI model efficiency and performance. Ability to identify use-cases for and develop predictive models to classify, segment, and interpret our users’ behavior.
• Optimization: Develop methodologies to explore/simulate the impact of new interventions and develop data products to optimize product/operational strategies.
• Communication: Deliver robust research reports and effective data visualizations. Collaborate with and present to stakeholders to identify opportunities and communicate findings, and drive impact.
• Empowerment: Think strategically about opportunities to improve and scale our brand measurement and customer insights.

Required qualifications

• 9+ years of industry experience in a quantitative analysis role with a Master’s degree in a quantitative field (math / economics / statistics, and etc.), or 6+ years of experience with a PhD degree.
• Strong knowledge of causal inference, experimentation, and statistical modeling.
• Skilled in statistical programming (Python or R) and database usage (SQL)
• Proven ability to communicate clearly and effectively to audiences of varying technical levels
• Ability to translate complex findings and results into compelling narratives that drive impact
• Excellent project management, communication, and teamwork skills
• Payments/Risk Domain expertise is a strong plus

Offices: United States