Associate Data Scientist

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, provide 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, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data and improve. 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.

Reporting to the Machine Learning Engineer-Manager, the Associate Machine Learning Engineer will analyze large datasets to extract meaningful insights.

What else you will do:

• Apply machine learning, data mining, and statistical techniques to uncover data value.
• Design efficient data structures and storage systems for optimal data manipulation and retrieval.
• Develop data-driven models to measure data value and validate performance.
• Conduct Return on investment analysis and document/present model processes and results.
• Collaborate to develop best practices for using data and creating insights.
• Manage independent assignments, influencing project outcomes and leading teams when needed.
• Develop positive client relationships by understanding their requirements and goals.
• Mentor team members and participate in the broader analytics community through presentations.

What you are expected to bring:

• Understanding of probability, statistical inference, optimization algorithms, linear algebra, and calculus.
• Proficiency in applying important analytical techniques, such as regression analysis, machine learning, AI, deep learning, and other advanced modeling approaches.
• Experience with model cross-validation techniques, including regularization and Bayesian shrinkage, and familiarity with statistical significance tests and Monte Carlo simulations.
• Proficient in writing code in general-purpose programming languages such as Python or C++.
• Understanding of modern big data technologies, including the Apache family (Hadoop, Spark), database technologies (e.g., Graph databases, time-series databases), and natural language processing tools for unstructured data analysis..
• Understanding of specific product domains and their application to client solutions.
• Experience working with different teams.
• Qualifications:
• Advanced degree or equivalent experience in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or related quantitative fields.
• Fluent in English, both written and spoken.

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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