This Mid-level Data Scientist role at Experian's Software Solutions Analytics Services Team is ideal for professionals with at least 3 years of experience in AI
Work type: hybrid
Location: Sofia
Type: Full-time
This Mid-level Data Scientist role at Experian's Software Solutions Analytics Services Team is ideal for professionals with at least 3 years of experience in AI, data science, or predictive modeling. You should have an advanced degree in a quantitative field and strong coding skills in Python, alongside expertise in Spark (preferably pySpark) for large data analysis. The role heavily emphasizes experience with Generative AI (LLMs) and various ML algorithms and open-source deep learning tools. You will be instrumental in developing advanced machine learning solutions, prototypes, and contributing to new product launches. This hybrid role in Sofia offers excellent work conditions, extensive professional development opportunities, a comprehensive social benefit package including a flex allowance and additional health insurance, and a focus on work-life balance with 25 days of paid vacation. You might be a good fit if you... * Have a strong background in predictive modeling and generative AI. * Are proficient in Python, Spark, and various ML/deep learning frameworks. * Enjoy collaborating with diverse teams to bring new solutions to market. * Thrive in a dynamic environment focused on innovation and product development.
## Job Description
<p>Our Experian Software Solution's Analytics Services Team supports analytic and generative AI products for decisioning, analytics, and fraud and identity globally.</p><p>As a <strong>Data Scientist</strong>, you will help develop analytical solutions and contribute to product prototypes using your predictive modeling skills, coding expertise, and Gen AI experience. You will apply analytic consulting skills to lead client and internal engagements for Experian's new global product launches and early client success efforts. You will report to the Director of Data Science and Gen AI.</p><p><strong>What you'll do:</strong></p><ul><li>Create advanced machine learning analytical solutions and prototypes to extract insights from diverse structured and unstructured data sources.</li><li>Collaborate with Engineering, Research, and Data Science teams in the design of Machine Learning, Dashboarding, Ad Hoc Analysis, and AI applications. We implement these applications in a cloud-native big data (AWS) computing platform.</li><li>Articulate model processes and outcomes, documenting and presenting findings and performance metrics, and translating complex findings into relevant insights.</li><li>Partner with Leaders, Analytic Consultants, Engineers, Account Executives, Product Managers, and external partners to bring new solutions to market that provide impact to Experian's broad client base.</li><li>Use Gen AI and model development tools to create new models.</li><li>Research and integrate new data assets from different sources into Experian's ML and AI platform.</li><li>Gather feedback from internal and external clients to guide new product development, feature prioritization, and product evolution of tools and capabilities supported by the Ascend Platform.</li><li>Dissect and document vast datasets, analyzing them to highlight patterns and insights.</li><li>Solve complex challenges by developing impactful algorithms.</li></ul>
## Qualifications
<p><strong>What you'll bring:</strong></p><ul><li>Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field.</li><li>3+ years of experience in AI, data science, or predictive modeling, with a track record for managing complex, hands-on analytical technology projects.</li><li>Statistical modeling proficiency in at least one programming language, with coding skills in Python, and familiarity with coding best practices.</li><li>Experience with large data analysis using Spark (pySpark preferred).</li><li>Experience with LLMs and the relevant tools in the Generative AI domain.</li><li>Experience with ML algorithms (e.g., XGBoost, GANs, clustering, graph algorithms, hyperparameter tuning)</li><li>Experience with open-source tools for deep learning and machine learning technology. such as pytorch, Keras, tensorflow, scikit-learn, pandas.</li><li>Experience applying Generative AI-based tools.</li><li>Experience with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, mongoDB, or Cassandra.</li><li>Experience modifying and applying advanced algorithms to address practical problems.</li></ul>