Lead Data Scientist at Experian

Sofia, Sofiya, Bulgaria -

Full Time

Start Date

Immediate

Expiry Date

03 Aug, 26

Salary

0.0

Posted On

05 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PySpark, AWS, Generative AI, Machine Learning, Spark, Hadoop, NoSQL, XGBoost, Statistical Modeling, Data Science Management, Model Risk Management, Big Data Cloud Platforms, Predictive Modeling, Analytical Prototyping, Data Analysis

Industry

Information Services

Description

Company Description Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Job Description The Data Science Lead will manage and mentor analytics team members while remaining hands-on with data science projects. Your role will involve leading EAMRM data science priorities, collaborating with cross-functional stakeholders, and ensuring alignment with regulatory and governance standards. You will also support innovation in GenAI and platform analytics, leveraging big data cloud platforms and advanced modeling techniques. You will report to the Director of Data Science and Gen AI. What you'll do: Lead and guide a team of innovation-focused data scientists. Partner with Leaders, Analytic Consultants, Engineers, Account Executives, Product Managers, and external partners to bring new innovative solutions to market that provide impact to Experian's broad client base Technical Execution-Develop and deploy models using Python or PySpark on big data cloud platforms (e.g., Ascend).Ensure adherence to model risk management and governance processes. Innovation & Strategy-Support GenAI and platform analytics innovation projects. Craft advanced machine learning analytical solutions and prototypes to extract insights from diverse structured and unstructured data sources. Articulate model processes and outcomes, documenting and presenting findings and performance metrics, and translating complex findings into actionable insights. Collaborate with Engineering, Research, and Data Science teams in the design and implementation of Machine Learning, Dashboarding, Ad Hoc Analysis and AI applications in a cloud-native big data (AWS) computing platform. Leverage Gen AI and model development tools to develop and maintain new models. Dissect and document vast datasets, analyzing them to highlight patterns and insights. Develop and assess analytic tools developed internally and externally. Stay informed about regulatory changes, technological advancements, and model risk management processes and controls to ensure the technology stack meets all compliance requirements. Research, integrate, and test new data assets and software from different sources into Experian's analytic platform. Gather feedback from internal and external clients to guide new product development, feature prioritization, and product evolution of tools and capabilities. Qualifications What you'll bring: 7+ years of experience in AI, data science, or predictive modeling, with a track record for managing complex, hands-on analytical technology, innovation, and client-focused projects. Data science team management experience preferred Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field Statistical modeling proficiency in at least one programming language, with coding skills in Python, and proficiency with distributed computing frameworks (AWS). Experience with large data analysis using Spark (PySpark preferred) and model development using Python or SAS Expertise with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, MongoDB, Cassandra. Solid understanding of ML algorithms (e.g., XGBoost, GANs, clustering, graph algorithms, hyperparameter tuning) Experience applying Generative AI-based tools and rapid prototyping of new concepts from ideation through early client success Proven experience managing analytics or data science teams. Additional Information What you will get: Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and books. Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time. Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits! Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event. Opportunity for Flexible working hours and Home Office. Experian is an Equal opportunity employer. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity. #LI-Hybrid This is a hybrid remote/in-office role. Experian Careers - Creating a better tomorrow together Find out what its like to work for Experian by clicking here Employee Status: Regular Role Type: Hybrid Department: Analytics Schedule: Full Time

Responsibilities

Lead and mentor a team of data scientists while remaining hands-on in developing and deploying ML models on cloud platforms. Collaborate with cross-functional stakeholders to deliver innovative AI solutions and ensure adherence to regulatory governance standards.