RepRisk
Jobs at RepRisk
Let Your Resume Do The Work
Upload your resume to be matched with jobs you're a great fit for.
Success! We'll use this to further personalize your experience.
Recently posted jobs
Big Data • Information Technology • Database • Financial Services
Lead execution and optimization of paid and organic social media campaigns (LinkedIn, Google Ads) to drive lead generation. Manage day-to-day campaign performance, testing, budget optimization, content quality, and reporting. Analyze results to recommend improvements and collaborate with Marketing, Sales, and Product stakeholders to align campaigns with commercial priorities.
Big Data • Information Technology • Database • Financial Services
As BDR Lead, you will build and lead a global team, design sales processes, ensure pipeline generation, optimize sales handovers, and evolve technology strategies for success.
Big Data • Information Technology • Database • Financial Services
As a Junior Research Analyst, you will analyze and input risk data related to ESG issues into the RepRisk database and assess incidents accordingly.
Big Data • Information Technology • Database • Financial Services
As BDR Lead, you will build a global team, drive pipeline generation, optimize sales processes, and ensure effective lead qualification between marketing and sales.
Big Data • Information Technology • Database • Financial Services
Lead the evolution of AI-powered systems, manage product strategy and client relationships, enhance data pipelines, and drive continuous product improvements.
Big Data • Information Technology • Database • Financial Services
Develop and maintain scalable data infrastructure and ETL pipelines, support machine learning applications, ensure data quality, and collaborate on data models.
Big Data • Information Technology • Database • Financial Services
As a Data Engineer, you will develop and maintain scalable data infrastructure for machine learning initiatives, automate data processing, ensure data quality, and collaborate across teams.
Big Data • Information Technology • Database • Financial Services
Build and enhance automated checks, frameworks, tooling and AI-assisted solutions to validate, observe, and improve data pipelines and services. Collaborate with engineering and data teams to detect, diagnose, and act on quality issues and improve developer experience.
Big Data • Information Technology • Database • Financial Services
Quota-carrying enterprise sales role owning full sales cycle for banks and asset managers. Build and convert multi-year pipelines, engage senior stakeholders, design solutions, lead complex deal negotiations, maintain CRM pipeline hygiene, and collaborate with Revenue Ops, Product, and regional teams to drive new business growth.
Big Data • Information Technology • Database • Financial Services
Quota-carrying enterprise sales role owning full sales cycle for banks, asset managers, and asset owners. Build and convert multi-year subscriptions, engage senior stakeholders across Risk, Compliance, Sustainability and IT, lead complex deal orchestration, maintain CRM hygiene and forecasting, and partner with Revenue Ops, BDRs, and Product to drive pipeline and inform GTM priorities. Regular travel (~20-25%).
Big Data • Information Technology • Database • Financial Services
Lead and develop a global team of Risk Data Analysts to ensure accurate, timely ESG risk data curation. Recruit, coach, and drive projects improving data processes, collaborate with HR and Product & Technology, and foster a high-performing, innovative team culture focused on data quality and execution.
Big Data • Information Technology • Database • Financial Services
As a Senior AI Engineer, you'll develop agentic systems, build AI integrations, and design production systems while ensuring compliance in high-stakes environments.
Big Data • Information Technology • Database • Financial Services
Design, build, and operate production-grade single- and multi-agent AI systems with planning, memory, tool-use, and auditability. Build MCP servers, LLM-powered microservices, and agentic workflows; implement observability, testing, and evaluation; integrate APIs and data pipelines; collaborate with product and domain experts and adopt state-of-the-art agent and LLM techniques.



