Data Scientist

We are currently looking for Data Scientist to join our growing Sofia based Analytics Team, established in 2007, as we are expanding our portfolio to support our North America Business.

As a Data Scientist, you will develop and validate robust analytical solutions for diverse clients – this includes ad hoc data analysis as well as development of statistical models for predicting and managing the behavior of consumers, utilizing machine learning techniques to enhance traditional credit risk models and improve predictive accuracy. You will be presenting results and business analysis to senior stakeholders (both internal and external) and support more junior team members in their day to day activities. You will report to Data Modeller-Manager.

What you will do:

• Develop, validate, and maintain credit risk models, including application, behavioral, and collection scoring models
• Utilize machine learning techniques to enhance traditional credit risk models and improve predictive accuracy
• Work with large, complex datasets to extract insights and build risk assessment frameworks
• Evaluate the performance of the trained models and presentation of the results to stakeholders
• Produce ad-hoc analysis on the developed models
• Work on proof-of-concept projects to support client needs
• Maintenance and improvement of the existing model development pipeline
• Research and development of new advanced analytics solutions

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, deliver digital 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 realise their financial goals and help them to save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agrifinance, insurance, and many more industry segments.

We invest in talented people and new advanced technologies to unlock the power of data and to innovate. A FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 23,300 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

What you will bring:

• 3+ years of experience in Data Science role
• A degree (BSc level) at a numerical discipline, such as Computer Science, Mathematics, Statistics and econometrics, Physics, etc.
• Strong grasp of probability, statistical inference, optimization algorithms, linear algebra, and calculus.
• Understanding of how and when to apply key analytical approaches including regression analysis and machine learning
• Ability to write near-production-level code in at least one general purpose programming language (e.g. Python, C++)
• To learn and understand new technologies
• Analytical and problem-solving abilities, coupled with an enquiring mind
• Experience with BI Tools such as Tableau and Power BI will be considered as an advantage.
• Fluency in English

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.

What you will get:

• Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.
• Social benefits package including life insurance, food vouchers, additional health insurance for you and a family member, monthly flex allowance including internet bill coverage, sick leave allowance, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many more!
• Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in social responsibility events.
• Opportunity for flexible working hours and home office.
• Personal Development - career pathways for professional growth supported by learning and development programmes and unlimited access to online educational training courses, learning materials and books.

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