Non-Financial Risk Analytics, Senior Associate

Who we are looking for

We are looking for a high‑energy, detail‑oriented Senior Associate to join our Non‑Financial Risk Analytics team, reporting to an Assistant Vice President. You will help deliver accurate, stakeholder‑ready risk analytics products (dashboards, recurring reports, extracts) and contribute to data science and predictive analytics work that strengthens how we monitor and anticipate non‑financial risk trends. Our work supports risk management across operational, technology/cyber, and compliance domains, where data quality and disciplined execution matter.  

The role can be performed from Krakow or Gdansk, Poland. The role is a hybrid opportunity, 3 days onsite, 2 days remote.

Primary Responsibilities 

• Produce and maintain recurring analytics deliverables (dashboards, reports, datasets) with strong controls, documentation, and cycle‑to‑cycle consistency.  

• Perform data validation and reconciliations; investigate discrepancies, trace issues to source, and document root cause and remediation actions.  

• Build and enhance Power BI dashboards based on prepared data models, following design standards and stakeholder needs.  

• Develop and support automation (Python/SQL-based) that replaces manual refreshes; assist with testing, monitoring, and controlled change implementation.  

• Contribute to data science and predictive analytics use cases (e.g., trend drivers, forecasting, anomaly signals, NLP exploration), and help translate results into clear, decision‑ready insights.  

• Proactively communicate risks to delivery (data delays, quality issues, unclear requirements) early and clearly; partner with the AVP on prioritization and stakeholder updates.  

Required Qualifications 

Functional / Domain 

• Basic to intermediate understanding of risk management concepts (deep expertise not required; genuine interest in learning is required).  

• Strong attention to detail and commitment to data accuracy and controlled reporting practices.  

• Experience working with large structured datasets (Excel, SQL, or similar), including reconciliations and root-cause tracing.  

Technical / Analytics 

• Python (intermediate): able to write and debug data processing scripts independently.  

• SQL: comfortable extracting, joining, filtering, and aggregating across relational datasets.  

• Power BI: able to build and maintain dashboards; implement measures and filters from a prepared model with guidance.  

• Excel (advanced): pivot tables, XLOOKUP/VLOOKUP, Power Query; able to support validation and controls.  

• Exposure to automation concepts (scheduled scripts, refresh cycles, testing and validation).  

Behavioral 

• Learning agility and comfort ramping quickly across a new domain, tools, and reporting cadence.  

• Structured problem‑solving: can diagnose issues, propose fixes, and escalate appropriately.  

• Ownership mindset and proactive communication—no surprises at deadline.  

Preferred Qualifications 

• Experience with predictive analytics or data science (coursework, projects, or applied work), including EDA, basic modeling (regression/classification/forecasting), and model evaluation concepts.  

• Familiarity with non‑financial risk programs such as incidents, issues/findings, KRIs, RCSA (or adjacent risk reporting).  

• Experience improving reporting workflows with governance discipline (version control, change management, documented sign‑offs).  

• Curiosity about AI/LLM tools and how they can support analytics workflows (with appropriate controls and review).  

Education & Experience 

• Bachelor’s degree (or equivalent practical experience) in a quantitative or technical field (e.g., analytics, data science, engineering, economics, finance, computer science). 

• Typically 3+ years experience in analytics/reporting, data engineering, risk analytics, or a related role.