Credit Portfolio Data Scientist - (Hybrid; 80%-100%) - (m/f/x/d)

<p><span><span>Are you looking for a challenge and an opportunity to further advance your skills and career in a great working environment? Are you passionate about applying your expertise in AI, machine learning, and big data to optimize risk and profitability in a global environment? Do you want to lead innovative projects that drive data-driven transformation and shape the future of underwriting at Swiss Re? Would you like to collaborate with top data scientists, actuaries, and engineers to develop innovative solutions that impact strategic decisions across Swiss Re? We are looking for a data scientist to join our Actuarial Portfolio Management, Credit and Surety team and this could be your opportunity.</span></span></p> <p> </p> <p><span><span><b>About the Role </b></span></span></p> <p> </p> <p><span><span>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.<br/> 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.</span></span></p> <p><br/> <span><span>Key Responsibilities:<br/> •    Contribute to steering and monitoring the portfolio in line with strategic objectives, maintaining oversight of the Global Surety portfolio performance across regions.<br/> •    Support activities related to the elaboration and implementation of the strategy for Actuarial Portfolio Management Credit &amp; Surety.<br/> •    Collaborate with cross-functional teams to develop innovative solutions that support data transformation, risk management, and underwriting efficiency.</span></span></p> <p><br/> <span><span><b>About the Team</b> </span></span></p> <p><br/> <span><span>We are a<b> friendly and collaborative</b> team, who always puts the <b>client first</b>. We partner with portfolio owners to provide the framework of proper portfolio steering and insights to make us more profitable. We focus on<b> data driven outcomes</b> to find new ways to solve challenges through quantitative models and data transformation. </span></span></p> <p><span><span>The Actuarial Portfolio Management Credit and Surety(APM C&amp;S) team reports directly to the Global Head of Actuarial Portfolio Management Corporate Solutions</span></span></p> <p> </p> <p><b><span><span>About You </span></span></b></p> <p> </p> <ul> <li>You have strong interpersonal skills and ability to maintain effective working relations in a multi-disciplinary and multi-cultural environment.</li> <li><span><span>You are a self-starter and organized, able to handle multiple priorities and meet deadlines. Ability to manage diverse projects and tasks simultaneously.</span></span></li> <li><span><span>You are able to apply quantitative skills, business knowledge, logical thinking and communicate the key message by visualization &amp; presentation</span></span></li> </ul> <p> </p> <p><span><span>Essentials</span></span></p> <ul> <li><span><span>6+ years of hands-on experience with PySpark and Python, particularly in building and optimizing large-scale data transformation pipelines.</span></span></li> <li><span><span>3+ years of SQL experience, comfortable writing and optimizing complex queries.</span></span></li> <li><span><span>Solid experience developing NLP solutions, with exposure to GenAI and unsupervised learning methodologies.</span></span></li> <li><span><span>Extensive experience in data visualization and developing interactive dashboards for business stakeholders, with a focus on strategic insights.</span></span></li> <li><span><span>Good understanding of statistical models and core statistical methods, like distributions, time series, etc</span></span></li> <li><span><span>Solid academic education (university degree or higher), ideally in financial economics, statistics, econometrics, financial engineering, or actuarial sciences.</span></span></li> <li><span><span>Advanced English communication skills, both written and verbal.</span></span></li> <li><span><span>Proven ability to work independently, solve complex problems, and drive business impact through data-driven strategies.</span></span></li> </ul> <p> </p> <p><span><span>Nice to haves</span></span></p> <ul> <li><span><span>Experience with Palantir Foundry or other big data platforms.</