Работа Data Scientist

86 нови обяви за работа

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Популярни търсения:

Data Scientist

Experian
location_on гр. София

icon 5,100 лв / месец (изчислена от Yox)

Пълно описание


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, 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 .

Job Description

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


Qualifications

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


Additional Information

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.


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.

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

Средна заплата за сектора


5,100 лв / месец (изчислена от Yox)

info-icon Средна работна заплата за града изчислена от YOX

минимална

500 лв / месец

максимална

700,000 лв / месец

Мнения и оценки от служители


3.4
Добра
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3.2
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Заплата и Придобивки
3.3
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Култура и Ценности
3.1
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Кариера и възможност за развитие
3.3
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Баланс между работата и живота
3.6
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Колеги
3.1
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Местоположение
3.6
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Стабилност
3.9
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Общо усещане
4.0
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Управление
4.0
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Толерантност и Равенство
2.3
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Работна среда

Изследовател на данни/изследователка на данни


Изследователите на данни намират и тълкуват богати източници на данни, управляват големи количества данни, обединяват източници на данни, осигуряват съгласуваност на наборите от данни и създават визуализации за подпомагане на разбирането на данните. Те изграждат математически модели като използват данни, представят и съобщават констатациите и откритията за данни на специалисти и учени от техния екип и, ако е необходимо, на неспециализирана аудитория, и препоръчват начини за прилагане на данните.

Необходими основни умения

  • съставяне на научни или академични документи и техническа документация
  • нормализиране на данни
  • управляване на изследователски данни
  • използване на техники за обработване на данни
  • тълкуване на текущи данни
  • взаимодейства професионално в научноизследователска и професионална среда

Необходими основни знания

  • проучване на данни
  • техники за визуално представяне
  • извличане на информация
  • статистика
  • категоризиране на информация
  • език за описание на търсене на мрежови ресурси

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