Senior Data Scientist
- Sofia
- Analytics
- Permanent
- Hybrid
- Full Time
Our Experian Software Solution's Analytics Services Team supports analytic and generative AI products for decisioning, analytics, and fraud and identity globally.
As a Senior Data Scientist, 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.
What you'll do:
- Create advanced machine learning analytical solutions and prototypes to extract insights from diverse structured and unstructured data sources.
- 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.
- Articulate model processes and outcomes, documenting and presenting findings and performance metrics, and translating complex findings into relevant insights.
- 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.
- Use Gen AI and model development tools to develop new models.
- Research and integrate new data assets from different sources into Experian's ML and AI platform. Develop and assess analytic tools developed internally and externally.
- 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.
- Dissect and document vast datasets, analyzing them to highlight patterns and insights.
- Solve complex challenges by developing impactful algorithms.
- Gather input from colleagues and management to address issues within project team.
- Lead and advocate efforts to improve client's analytical solution, data quality, model fit, and project timeline
- Work with the product management team to provide expert advise and define the go-to-market strategy for new products and services based on the new data science models/ methodologies
- Participate in the greater analytical community through conference presentation and white paper
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 accomplish 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. Learn more at experianplc.com.
What you'll bring:
- Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field.
- 4+ years of experience in AI, data science, or predictive modeling, with a track record for managing complex, hands-on analytical technology projects.
- Statistical modeling proficiency in at least one programming language, with coding skills in Python, and familiarity with coding best practices.
- Experience with large data analysis using Spark (pySpark preferred).
- Experience with LLMs and the relevant tools in the Generative AI domain.
- Experience with ML algorithms (e.g., XGBoost, GANs, clustering, graph algorithms, hyperparameter tuning).
- Experience with open-source tools for deep learning and machine learning technology. such as pytorch, Keras, tensorflow, scikit-learn, pandas.
- Experience applying Generative AI-based tools.
- Experience with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, mongoDB, and Cassandra.
- Experience modifying and applying advanced algorithms to address practical problems.
- Fluent English – written and spoken.
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
Explore Experian's award winning 'people first' culture.
Being part of Experian is exciting. Every day brings new challenges, new opportunities, new ways for us to do what we do best: using our innovative technologies and data to work in new and surprising ways. All brought together in a single thought: Discover the Unexpected.
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