Role Description Greenhouse is looking for a Data Scientist to join our team! As a Data Scientist within our Corporate Development and Analytics department, you will join a multidisciplinary team of data scientists and business analysts dedicated to driving Greenhouse’s data strategy by building sophisticated data products. Serving as the bridge between raw product output and executive level decision making, you will partner upstream with Product teams to architect foundational telemetry, ensuring that every new feature is instrumented for deep dive analysis from day one. You will solve complex user pain points and ensure our long-term roadmap is backed by proactive, informed data productization. Who will love this job - A Connector – You bridge the gap between complex statistical findings and actionable executive strategy to influence long-term roadmaps. - A Technical Specialist – You take pride in writing high quality, production ready code and applying engineering best practices to every data pipeline. - A Cross-functional Partner – You thrive when working alongside product and data platform teams to solve user pain points through shared expertise. - A Data Strategist – You prioritize a data-first approach, ensuring that telemetry and tracking are integrated into every stage of the product lifecycle. - An Analyst – You are energized by deep dives into data to uncover the core drivers of customer retention and product adoption. - A Builder – You enjoy creating scalable, automated analytical frameworks that replace manual tasks with long-term efficiency. What you’ll do - Communicate complex technical findings to executive leadership to influence Greenhouse's long-term roadmap. - Partner with Product Managers to identify opportunities where data science can solve user pain points. - Conduct deep-dive statistical analysis to uncover the drivers of customer retention and product adoption. - Design, write, and maintain production-quality code (Python or SQL) to build scalable data pipelines, automated analyses, and predictive models. - Write complex, highly optimized SQL queries to extract, clean, and transform large-scale datasets from cloud data warehouses (e.g., Snowflake, Redshift, or BigQuery). - Apply software engineering best practices to data science workflows, utilizing version control (Git), code reviews, and orchestration tools to ensure robust and reproducible analyses. - Interface with distributed analysts to provide guidance on complex modeling and advanced statistical techniques. - Advocate for data-first product design, ensuring that telemetry and event tracking are prioritized during the feature development lifecycle. Qualifications - 3-6 years of experience as a data scientist, analytics engineer, or product data analyst. - Demonstrated experience working within a B2B business model. - Proven track record of building scalable analytical frameworks and automated reporting suites that bridge technical data stacks with business outcomes. - Documented success in translating raw product output into insights that influence long-term executive roadmaps. - Expertise in writing complex SQL queries. - Proficiency using programming languages (Python or SQL) for data manipulation, statistical modeling, and analysis. - Experience with Version control (Git), and orchestration tools. - Strong ability to work cross-functionally with Product teams to identify opportunities where data science can solve user pain points. - Your own unique talents! Your background has given you a unique perspective and set of transferable skills that aren't always in alignment with a given role - but those are qualities we value at Greenhouse. Requirements - Applicants must be legally eligible to work in Canada as of the start date chosen by the Company. We are unable to support sponsorship at this time. Benefits - The national pay range for this role is $105,800 - $132,300 CAD. Individual compensation will be commensurate with the candidate's experience and qualifications. - Certain roles may be eligible for additional compensation, including stock option awards, bonuses, and merit increases. - Additionally, certain roles have the opportunity to receive sales commissions that are based on the terms of the sales commission plan applicable to the role.

Role Description - Develop trade analytics solutions for compliance, risk scoring, and evasion detection (AD/CVD, transshipment, forced labor) - Work with CBP systems (e.g., ACE) and support DHS mission objectives - Build and optimize data pipelines using Databricks, Spark, and Delta Lake - Design, train, and deploy ML/AI models using MLOps frameworks (MLflow, Kubeflow, CI/CD) - Develop and implement GenAI solutions (RAG, prompt engineering, fine-tuning, agentic workflows) - Apply explainable AI (XAI) techniques and Responsible AI frameworks (NIST AI RMF) - Deliver secure solutions in AWS GovCloud or Azure FedRAMP environments - Support ATO processes and ensure compliance with federal security standards - Manage Agile tasks independently, including backlog ownership and stakeholder communication Qualifications - Experience with CBP/trade systems (ACE, AD/CVD, tariff enforcement) OR background in financial crimes, forensic analysis, or intelligence planning is preferred - Hands-on expertise in Databricks, Apache Spark, and Delta Lake - Strong MLOps experience (MLflow, Kubeflow, CI/CD for ML models) - Experience with LLMs (RAG, fine-tuning, prompt engineering, GenAI deployment) - Knowledge of Explainable AI (SHAP, LIME) and Responsible AI frameworks - Experience working in AWS GovCloud or Azure FedRAMP (IL2+) environments - Familiarity with ATO and secure federal data environments - Ability to work independently with minimal supervision in federal programs - Strong communication and stakeholder management skills

Role Description The Engagement Manager II (EM II) is a delivery leadership role within the organization. The individual manages one or more projects/project teams/programs at a time. The Engagement Manager owns customer expectations, ensures delivery assurance for application services deliverables, and drives overall client outcomes. The EM role quantifies the business benefits of project outcomes throughout the engagement. As a more advanced Engagement Manager position, an EM II is expected to have the experience and background to perform all the duties described below for engagements of all service types, including: - Complex deliverable-based, fully outsourced, or large-scale engagements or programs. - A more demanding set of skills, an educational background, and demonstrated experience in the technical practice area. Qualifications - Bachelor’s or Master’s degree in Computer Science (other majors acceptable with requisite experience). - 13+ years of experience in information technology and professional services at a consulting services technology provider. - At least 10+ years of project management experience, of which at least 4+ years were performed as a technical project manager. - Proven experience in planning, executing, and overseeing data-related projects. - Expertise in project management methodologies (Agile, waterfall) and tools (e.g., Jira). - Strong understanding of development principles, including data, life cycle, quality, governance, security, and ethics. - Certification in AWS, Azure, or Google Cloud preferred. - 4+ years of development experience is a must. - Experience in enterprise architecture and solution design. - Hands-on leadership and end-to-end ownership of leading and delivering platforms and products by leveraging a modern technology stack (Cloud, DevOps). - Knowledge of Data technologies like Data Warehousing or Cloud experience preferred. - Excellent experience with MS Office (Excel, Word, PowerPoint). - PMP or other project management certification (e.g., Scrum Certified) preferred. Requirements - Possess incredible degrees of situational awareness with a ‘Customer First Mindset.’ - Excellent oral and written communication skills, analysis and problem-solving skills, and excellent time management and organizational skills. - Demonstrated experience communicating and presenting at senior executive/director levels. - Superior people and personnel management skills. - Active and passionate role in their own personal and professional development. - Recognizes own strengths and weaknesses; admits mistakes; proactively seeks feedback from others. Benefits - Medical, Dental, and Vision. - Critical Illness, Accident, and Hospital. - 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available. - Life Insurance (Voluntary Life and AD&D for employee and dependents). - Short and Long-Term Disability. - Health Spending Account (HSA). - Transportation Benefits. - Employee Assistance Program. - Time Off/Leave (PTO, Vacation or Sick Leave). Company Description TEKsystems Global Services (TGS) is the growth solution for enterprises today. We unleash growth through technology, strategy, design, execution, and operations with a customer-first mindset for bold business leaders. We deliver cloud, data, and customer experience solutions. Our partnerships with leading cloud, design, and business intelligence platforms fuel our expertise. We value deep relationships, dedication to serving others, and inclusion.

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: STEM QA Reviewer — Materials Engineering Type: Contract Compensation: $90/hour Location: Remote Duration: 3-week engagement (6/5–6/25) Role Responsibilities - Evaluate STEM problem prompts and verify golden answers for accuracy and clarity. - Assess grading methodology and ensure robustness in evaluation criteria. - Analyze and summarize model agent trajectories for best and worst rollouts. - Provide structured feedback using standardized review forms to improve training data quality. - Render Accept/Revise/Reject verdicts with detailed explanations to enhance AI model performance. - Self-select problems within your domain expertise and work independently on the HFI (Surveyor) platform. Qualifications - MS or PhD in Materials Science / Materials Engineering or closely related field. - Ability to independently verify ground truth solutions for grad-level materials problems. - Strong scientific reasoning and written communication skills. - ~2.5 reviews per week (~2-4 hours per review). Requirements - Application Process (Takes 20–30 mins to complete): - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: Interview Process - For any help or support, reach out to: support@mercor.com - PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.