Financial & Data Modeler
AI summary
DFCU Bank is hiring a Financial & Data Modeler in Kampala, Uganda. The role involves designing, developing, validating, and maintaining financial models across credit, market, operational, price, and liquidity risk areas. Candidates should hold a degree in Mathematical Finance, Financial Engineering, Mathematics, Statistics, or Quantitative Economics, with strong quantitative and programming skills.
- Full-time role based in Kampala, Uganda
- Requires degree in Mathematical Finance, Financial Engineering, Mathematics, Statistics, or Quantitative Economics
- 1–2 years of relevant experience in credit or market risk model development or validation preferred
- Strong programming skills in Python/R, SQL, and Visual Basic required
- Professional qualifications such as FRM, CFA, or ACCA are an added advantage
AI job guide
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AI salary guide
Not enough public dataNot enough public salary data is available for this exact role. Before applying, prepare to ask about gross pay, benefits, contract length, probation period, transport and any allowances.
Can you qualify for this role?
- Required1+ years of relevant experienceThe job post includes a minimum experience signal.
- RequiredEducation or certification mentioned in the postThe captured text mentions education, a diploma, certificate, or licence.
- PreferredPractical evidence in no_experience, sem_experiencia, financeThe tags and summary point to skills connected with this role.
- RequiredAvailability to work in Not specifiedThe vacancy is associated with this location.
- UnclearComfort with the Full Time contract termsConfirm hours, duration, probation and benefits at the original source.
Documents to prepare
- Likely requiredUpdated CV
- Role specificCover letter or short employer message
- OptionalProfessional references
- Role specificAcademic or professional certificates
- VerifyID or passport only after verifying the employer
Application tips for this job
- Place your strongest Financial & Data Modeler evidence in the first half of your CV.
- In your cover letter or employer message, connect your experience to DFCU Bank and the role in Not specified.
- Add concrete examples related to no_experience, sem_experiencia, finance, ideally with measurable outcomes or clear responsibilities.
- Follow the instructions from BrighterMonday Uganda; avoid sending documents to unofficial contacts or copied links.
- Confirm the deadline, interview location and employer contact before sharing personal documents.
- Prepare a polite question about pay, benefits and contract terms for later interview stages.
Source and safety check
- BrighterMonday Uganda
- Original source link available
- Application method is clear
- Deadline not specified
- No major risk signal was detected in the captured text.
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Interview preparation
- What experience makes you a strong fit for this Financial & Data Modeler role in no_experience, sem_experiencia?
- How have you handled responsibilities similar to those in this job post?
- Are you available to work in Not specified under the listed contract or schedule?
- Prepare examples with clear responsibilities, tools used and measurable outcomes.
- Review the source and research DFCU Bank before the interview.
Ask what the first priorities will be in the role and how success will be measured.
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Original source description
- D
- Financial & Data Modeler
- DFCU Bank
- Engineering & Technology
- Today
- New
- Kampala
- Full Time
- Banking, Finance & Insurance
- Confidential
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Experience
- Level:
- No
- Length:
- No Experience/Less than 1 year
- Language Requirement:
- English
- Working Hours:
- Full Time - 8 to 5
- Applicant
- Location:
- Uganda
- Job descriptions &
- REQUIRED:
- Bachelor of Science or master’s degree in Mathematical Finance, Financial Engineering, Mathematics, Statistics and Quantitative Economics/Econometric.
- Professional qualification in such as (FRM, CFA, ACCA) is an added advantage.
- Other qualifications, certifications, or professional memberships that relate to financial engineering, financial modelling, data Analytics, Machine Learning and Data Governance.
- One to two years of relevant
- in Credit Risk, Market Risk model development or model validation/vetting team at a major Financial institution.
- Knowledge of Financial products and their modelling and calibration in both risk–neutral and real world across a wide range of products.
- Creativity in problem solving.
- Excellent Mathematical and Statistical skills.
- Solid knowledge of common practices in credit risk, marker risk and operational risk, including (PD, LGD, EAD, VAR, LDA, Economic Capital) methodologies.
- Solid programming skills (e.g., Python/R, SQL, Visual Basic). Knowledge of other programming languages is an added advantage.
- with numerically stress testing techniques is an asset.
Requirements
KNOWLEDGE, SKILLS, AND
Key Accountabilities
Design/develop/validate/deliver/review/maintain and enhance financial models in the following risk areas, Credit risk (e.g., AIRB, IFRS 9, Early warning, and credit scoring models), Market risk (e.g., VAR (Value at Risk), EAR (Earnings at Risk) models), Operational risk, Price risk (e.g., Risk based pricing models) and Liquidity risk based on industry best practices.
Support and work collaboratively with other quantitative and analytical areas such as forecasting and stress testing, customer behaviour modelling, and new innovations such as Machine Learning and Artificial Intelligence.
Train end users to ensure that they are well equipped to run and make strategic decisions from model outputs.
Prepare and Communicate model development documents (e.g., Model development plans, Model development technical documents and User guides) to key stakeholders.
Ensure adherence to the model development policy, data governance framework, policies, and procedures.
Ensure financial models adhere to the defined and agreed service level agreements (SLAs).
Keep up to date with the latest technical developments within financial modelling and engineering and making sure that changes to the industry’s best practice are adopted project team.
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