ML Ops Engineer

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

We are the leading global information services company, providing data and analytical tools to our clients around the world. We help businesses to manage credit risk, prevent fraud, target marketing offers and automate decision making. We also help people to check their credit report and credit score and protect against identity theft.

We employ approximately 17,000 people in 37 countries and our corporate headquarters are in Dublin, Ireland, with operational headquarters in Nottingham, UK; California, US; and São Paulo, Brazil.

Experian is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status.

We are committed to building an inclusive culture and creating an environment where people can balance successful careers with their commitments and interests outside of work. Our flexible working practices support our belief that this balance brings long-lasting benefits for our business as well as our people. Some roles lend themselves to flexible options more than others, and if this is important to you, we are open to discussing agile working opportunities during the hiring process.

We're currently looking for a ML Ops Engineer to join the R&D Team, part of our Analytics Center of Expertise. The team is focused on rolling out Trusso, our cutting-edge ML based transaction categorization engine across the world. If working on a truly global product that is likely to also impact you directly is something you have always wanted to do drop us your CV and let us do the rest.

Responsibilities:

• Oversee and facilitate the training of a range of Machine Learning models
• Evaluate the quality of the trained models, using existing and also new measures which the ML Ops Engineer will create
• Automate repetitive tasks and processes pushing leaving time for the truly challenging tasks and activities
• Report on the current and historical state of our models’ performance, along with issues and progress
• Perform Quality Assurance on the training data produced by our models, and provide feedback to the teams producing our training data, given your QA findings
• Assist our Data Scientists with testing, coding and UX
• Document parts of the modelling and testing process
• Deploy signed-off models in the production environment
• Investigate complex production issues, recreating problems and utilizing trace files & error diagnostics. Identify root cause and propose solutions

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, MatplotLib)
• 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)
• Exposure to Linux
• Good knowledge of OOP principles, data structures, algorithms & design patterns
• Knowledge in container-based deployment technologies (Docker and Kubernetes)

Any of the following abilities and skills will be considered an advantage:

• Knowledge and appreciation of agile development methodologies and techniques
• Experience with Apigee for APIs management
• Experience with automation packages, such as Luigi and make
• Knowledge of good software development practices (Test-driven Development, Clean Code, Refactoring, etc.)
• 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.
• Experience with DB technologies (PostgreSQL, MongoDB, etc.)
• Experience with CI/CD process development

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, 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

 In order to stay safe and be responsible, we introduce a remote hiring process with online interviews for all candidates.