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Работа в България?
Space Tower, бул. Цариградско шосе 86, София

Experian България

София

Machine Learning Engineer

Описание на длъжността

Machine Learning Engineer

  • Boulevard Tsarigradsko shose 86, 1113 Geo Milev, Sofia, Bulgaria
  • Full-time
  • Department: Analytics
  • Role Type: Hybrid
  • Employee Status: Regular
  • Schedule: Full Time

Company Description

Experian is the world’s leading global information services company. During life’s big moments — from buying a home or a car to sending a child to college to growing a business by connecting with new customers — we empower consumers and our clients to manage their data with confidence.

We have 20,000 people operating across 44 countries. By investing in our people, technology and innovation, we can help transform businesses, help communities prosper, enable more people to feel included in the financial opportunities that should be available to them, and help people to thrive. We're looking for inspired employees that want to make an impact on people and business.

Why us?

No one makes sense of data like Experian. We are on a mission to deliver the full power of data, analytics and technology in ways that transform lives. As a team, we’re committed to working together. So, we work in an inclusive environment that welcomes people with lots of different perspectives. We put people first and care about work that works. We like to strike a balance between how much time we spend on work and how much we keep for ourselves. After all, we’ve all got commitments and interests outside the office. So, talk to us about how you’d best like to work with us. We’re flexible and interested in helping you to get the best out of working with us.

Изисквания за длъжността

Job Description

We’re currently looking for a Machine Learning Engineer to join our R&D Team.

Responsibilities:

  • Work on new Machine Learning models implementation in collaboration with Data Scientists
  • Support product development by creating new features and automating processes
  • Build and maintain scalable solutions in production environment
  • Onboard new clients and support the integration of the solution on client-side
  • Document new services and features
  • Investigate complex production issues, recreating problems and utilizing trace files & error diagnostics. Identify root cause and propose solutions

Qualifications

Requirements:

  • BSc level degree at a numerical discipline, such as Computer Science, Maths, Statistics, Physics or related discipline
  • Working knowledge of Python – preferably both Python’s own syntax but also some of its main analytical packages (such as Pandas, Numpy, Scikit-learn)
  • Flexible and adaptable to learn and understand new technologies
  • Demonstrable analytical and problem-solving abilities, coupled with an enquiring mind and the ability to learn quickly
  • A keen eye for detail, good at spotting problems and quickly proposing solutions
  • Strong verbal and written communication skills (fluency in English)
  • Any of the following abilities and skills will be considered an advantage:
  • Knowledge and appreciation of agile development methodologies and techniques
  • Knowledge in container-based deployment technologies (Docker, Kubernetes, and OpenShift)
  • Experience with Apigee for APIs management
  • Basic knowledge of statistics and of measures used for evaluating performance of Machine Learning models, such as precision, recall, etc.
  • Basic understanding of Data Science concepts such as overfitting, cross-validation, test-vs-train split, etc.
  • Exposure to Linux.

Additional Information

 We offer:

  • Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials & book
  • Work environment - excellent work conditions with friendly environment, recognized strong team spirit, and fun and quality recreation time
  • Social benefit package - life insurance, monthly flex allowance, food vouchers, additional health insurance, corporate discounts, Multisport card, and a Share options scheme
  • Work-life balance - 25 days paid vacation and 3 additional paid days for participation in Social responsibility event
  • Opportunity for Flexible working hours and Home Office

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