CREDIT PORTFOLIO DATA SCIENTIST - (HYBRID; %) - (M/F/X/D) | MADRID, ES
Descripción de la oferta de empleo
About the Role You will not only contribute to the analysis of the credit and surety portfolio, from both risk and profitability perspectives, through the advanced analysis of internal and external data, but also work to make underwriting more efficient.
You will collaborate with teams across Swiss Re to drive data-driven transformation and solve complex data challenges using cutting-edge technology, ensuring sustainable and profitable business outcomes.
This is a unique opportunity to apply your deep knowledge of data science and analytics to real portfolios, connect economic trends to market performance, and investigate patterns to ensure long-term profitability.
You will also gain valuable exposure to credit portfolio management, bridging the gap between insurance and banking.
In this role, you will work closely with colleagues from various departments, including underwriting, finance, operations, claims, risk management, and actuarial functions.
Key Responsibilities.
⢠Contribute to steering and monitoring the portfolio in line with strategic objectives, maintaining oversight of the Global Surety portfolio performance across regions.
⢠Support activities related to the elaboration and implementation of the strategy for Actuarial Portfolio Management Credit & Surety.
⢠Collaborate with cross-functional teams to develop innovative solutions that support data transformation, risk management, and underwriting efficiency.
About the Team We are a friendly and collaborative team, who always puts the client first.
We partner with portfolio owners to provide the framework of proper portfolio steering and insights to make us more profitable.
We focus on data driven outcomes to find new ways to solve challenges through quantitative models and data transformation.
The Actuarial Portfolio Management Credit and Surety(APM C&S) team reports directly to the Global Head of Actuarial Portfolio Management Corporate Solutions About You • You have strong interpersonal skills and ability to maintain effective working relations in a multi-disciplinary and multi-cultural environment.
• You are a self-starter and organized, able to handle multiple priorities and meet deadlines.
Ability to manage diverse projects and tasks simultaneously.
• You are able to apply quantitative skills, business knowledge, logical thinking and communicate the key message by visualization & presentation Essentials • 6+ years of hands-on experience with PySpark and Python, particularly in building and optimizing large-scale data transformation pipelines.
• 3+ years of SQL experience, comfortable writing and optimizing complex queries.
• Solid experience developing NLP solutions, with exposure to GenAI and unsupervised learning methodologies.
• Extensive experience in data visualization and developing interactive dashboards for business stakeholders, with a focus on strategic insights.
• Good understanding of statistical models and core statistical methods, like distributions, time series, etc • Solid academic education (university degree or higher), ideally in financial economics, statistics, econometrics, financial engineering, or actuarial sciences.
• Advanced English communication skills, both written and verbal.
• Proven ability to work independently, solve complex problems, and drive business impact through data-driven strategies.
Nice to haves • Experience with Palantir Foundry or other big data platforms.
• Experience with JavaScript, particularly building interactive visualizations using D3.
s.
• Previous experience in credit quantitative models, credit portfolio management, risk management in banking or insurance is a plus.
• Experience working in an Agile environment, collaborating with cross-functional teams to deliver business outcomes.
• Good knowledge and understanding of credit aggregation, global macroeconomics, financial markets and credit-related products; experience in the Trade Finance and Surety sectors a plus • Fluency in Portuguese For Spain, the base salary range for this position is between EUR and EUR for a full-time role.
The specific salary offered considers.
⢠the requirements, scope, complexity and responsibilities of the role, ⢠the applicant's own profile including education/qualifications, expertise, specialisation, skills and experience.
In the situation where you do not meet all the requirements or you significantly exceed these, the offered salary may be below or above the advertised range.
In addition to your base salary, you may be eligible for additional rewards and benefits including an attractive performance-based annual bonus.
About Swiss Re Corporate Solutions Swiss Re is one of the world's leading providers of reinsurance, insurance and other forms of insurance-based risk transfer.
We anticipate and manage risks, from natural catastrophes and climate change to cybercrime.
Swiss Re Corporate Solutions is the commercial insurance arm of the Swiss Re Group.
We offer innovative insurance solutions to large and midsized multinational corporations from our approximately 50 locations worldwide.
We help clients mitigate their risk exposure, whilst our industry-leading claims service provides them with additional peace of mind.
Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking.
Swiss Re Corporate Solutions embraces a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics.
In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.
If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience.
Keywords.
Reference Code.
Detalles de la oferta
- Swiss Re
- Sin especificar
- 20/12/2024
- 20/03/2025
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