Job Description
The role involves developing machine learning solutions for financial risk management.
Key Responsibilities:
* Develop ML solutions for credit risk, market risk, and operational risk management.
* Build data pipelines for large-scale historical financial datasets.
* Utilize statistical modelling, predictive analytics, and supervised/unsupervised ML methods.
Technical Requirements:
1. Strong experience in developing ML solutions for financial or risk management domains.
2. Expertise in statistical modelling, predictive analytics, and supervised/unsupervised ML methods.
3. Familiarity with big-data and distributed technologies such as Spark, Hadoop, Databricks, or Snowflake.
4. Competent programming skills (Python mandatory; R or Java/Scala helpful).
5. Experienced in modern MLOps tools and methods.
6. Skilled in containerization and orchestration technologies.
Business Acumen:
* Deep understanding of banking/financial services industry.
* Familiarity with regulatory requirements.
* Experience dealing with cross-functional stakeholders.
Qualifications:
1. Master's or PhD in a quantitative discipline.
2. 7–10+ years of relevant industry experience with at least 3–5 years in a leading or senior role in ML projects.
Benefits:
* Pay rate between €500-€700 per day (subject to experience).
* 6-Month Contract.
* Opportunity to work with a reputable Fortune 100 organisation within the financial industry.