Jobs at Klar

Support the Talent Acquisition team in full-cycle recruitment: sourcing, interviewing, and selecting candidates; coordinate with hiring managers; manage high-volume applications; schedule interviews; and ensure an excellent candidate experience in a hybrid Mexico City role.

Lead sales enablement end-to-end: design onboarding, create sales content, optimize sales processes and tools (HubSpot, Cooby), measure enablement KPIs, and manage knowledge resources while partnering cross-functionally to boost sales productivity.

Generate outbound B2B leads, qualify prospects, schedule qualified meetings, and build a pipeline for Klar Empresarial. Use CRM and sales tools to prospect via calls, WhatsApp, email, and LinkedIn, tailor pitches to client needs, collaborate with Growth & Product, and meet enrollment and credit approval targets.

Own end-to-end B2B credit vertical: design and automate credit policies and underwriting engines, monitor portfolio KPIs, build data pipelines and BI dashboards, and partner with Product, Engineering, Data, Growth, and Sales to balance growth with risk.

Analyze B2B revenue performance, build reports and dashboards, automate operational processes, support CRM and customer lifecycle initiatives, and collaborate cross-functionally to improve adoption, retention and scalability.

Lead and scale a B2B commercial team to drive SME acquisition for Klar Empresarial. Own full sales motion, set commercial strategy, hit activation targets, maintain pipeline health, develop playbooks, and collaborate cross-functionally with RevOps, Marketing, Partnerships, Underwriting, and Customer Success.

Drive B2B revenue by prospecting, qualifying, demoing, and closing SME clients. Manage full sales cycle, maintain CRM records, collaborate with product/marketing/customer success, and meet sales quotas while shaping the new B2B pipeline.

Lead business strategy and project initiatives for credit products; analyze data to improve and automate processes using SQL, Python, Excel, and AI; define KPIs, produce recommendations, manage projects, and mentor junior teammates.

Execute, optimize, and scale paid acquisition across Google and Meta. Manage daily campaign operations, tracking, attribution, and pixel health. Build reports, run A/B tests, collaborate with creative and product teams, and improve CAC, ROAS, and funnel conversion while managing multi-million monthly budgets.

Support operations and analytics by performing data analysis, presenting findings, identifying improvement opportunities, automating processes, and executing manual operations using internal tools. Collaborate cross-functionally and communicate insights to drive business decisions.

Lead the bank's Internal Audit function, develop and execute a risk-based audit plan, evaluate controls and compliance (including AML and information security), report findings to the Audit Committee, coordinate with regulators and external auditors, monitor remediation, and lead and develop the internal audit team.

Design, build, and operate backend services for the loan lifecycle (offer, disbursement, accrual, repayment, write-off). Implement APIs, Kafka event producers/consumers, DB migrations, and tests; ensure financial correctness, observability, and collaborate with Risk, Data Science, Product, and Accounting.

Design, build, and optimize ML models for origination, scoring, limit management, and early-warning systems using alternative data. Deploy, monitor, and retrain models at scale, explore novel architectures, own models end-to-end, and communicate findings to stakeholders.

Manage and grow broker and strategic partner relationships through in-person visits, product adoption, retention playbooks, upsell/cross-sell, performance analysis, and cross-functional collaboration to drive portfolio growth and revenue.

Design, build, and maintain ML models and data pipelines to support AML and business decisions. Ensure data quality, automate processes, generate KPI reports, analyze large datasets, and communicate insights to cross-functional stakeholders.

Use SQL and Python to analyze customer behavior, design and evaluate experiments, build simple predictive models, automate KPI reporting and dashboards, and collaborate cross-functionally to drive growth and lifecycle strategies.