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. Learn more at experianplc.com.

Job Description

We are currently looking for Senior Data Modeller 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 Senior Data Modeller, you will develop and validate 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. You will present results and business analysis to senior stakeholders (both internal and external) and support more junior team members in their daily activities. You will report to Data Modeller-Manager.

 

What you will do:

Data extraction and data processingDevelop, manage credit risk models, including application, behavioral, and collection scoring modelsEvaluate the performance of the trained models and presentation of the results to stakeholdersProduce ad-hoc analysis on the available datasets or developed modelsWork on proof-of-concept projects to support client needsOversee the day to day work of more junior team membersIdentify opportunities for automation and follow them through internally within the team and towards external stakeholders

 

Qualifications

What you are expected to bring:

A degree (BSc level) in a numerical discipline, such as Computer Science, Mathematics, Statistics and econometrics, Physics3+ years of working knowledge in Python – preferably both Python's own syntax but also some of its main analytical packages (such as Pandas, Numpy, scikit-learn)Understanding of how and when to apply analytical approaches including regression analysis and machine learningGrasp of probability, statistical inference, optimization algorithms, linear algebra, and calculusGood at spotting problems and quickly proposing solutionsExperience with BI Tools such as Tableau and Power BI will be considered as an advantageFluency in English

Additional Information

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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