Associate Machine Learning Scientist

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Job Description

As Associate Machine Learning Scientist you will work on advanced research and development, to enhance relationships with clients, acquire strategic datasets and provide new solutions through product prototyping.

You will concentrate on new data asset evaluation and acquisition and new product prototyping. This will involve inventing and modifying advanced innovative algorithms, and applying them to large datasets to solve difficult business problems. You will balance and prioritise multiple concurrent projects, anticipate obstacles, and make high quality deliveries.

You will report to Director of Data Science and Gen AI.

What you'll do:

- Analyze, evaluate, and document large data sets
- Identify and apply appropriate machine learning/data mining/text mining techniques to uncover the value of the data
- Design data structure and data storage schemes for efficient data manipulation and information retrieval
- Develop tools for data processing and information retrieval
- Develop data-driven models to measure the value of a given data set
- Validate score performance
- Conduct ROI and benefit analysis
- Document and present model process and model performance
- Apply analytical and industry knowledge to construct analytical solutions with details for internal and external clients to solve their business problems.
- Be connected to clients, competitors, relevant market groups, to be aware of and understand movements, trends, up-coming opportunities and risks.

Qualifications

What you'll bring:

- Grasp of probability, statistical inference, optimization algorithms, linear algebra, and calculus.
- Understanding of how and when to apply necessary analytical approaches including regression analysis, machine learning, AI, deep learning and other advanced modeling approaches to extract and automate insights from data.
- Grasp of techniques for model cross-validation and penalizing unnecessary complexity, including regularization, Bayesian shrinkage, in-sample vs out-of-sample. Fluency with statistical significance tests and Monte Carlo simulation.
- Experience writing near-production-level code in at least one general purpose programming language (e.g. Python, C++).
- Understanding of Apache family (Hadoop, Spark), latest database technologies (e.g. Graph databases, time-series databases), and natural language processing and other tools for the parsing of unstructured data.

Additional Information

What you'll get:

- Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and book.
- Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.
- Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!
- Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.
- Opportunity for Flexible working hours and Home Office.

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.

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