Senior Machine Learning Engineer

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, create 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 realize their financial goals and help them 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. 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. Learn more at experianplc.com.

Job Description

Job description

Key Responsibilities

• Assist in Developing and Deploying Machine Learning Models: Support the development and deployment of machine learning models, including data preprocessing and performance evaluation in Python using sklearn, numpy and other standard libraries.
• Build and Maintain ML Pipelines: Help build and maintain scalable ML pipelines, and assist in automating model training workflows in Python using MLFlow, Databricks, Sagemaker or equivalent.
• Collaborate with Cross-Functional Teams: Work with product and data teams to align ML solutions with business needs and objectives.
• Write Clean and Documented Code: Write clean, well-documented code, following best practices for testing and version control. Use Sphinx and other auto documentation solutions to automate document generation.
• Support Model Monitoring and Debugging: Assist in monitoring and debugging models to improve their reliability and performance.
• Participate in Technical Discussions and Knowledge Sharing: Engage in technical discussions, code reviews, and knowledge-sharing sessions to learn and grow within the team.

Day-to-Day Activities

On a daily basis, you will work closely with senior ML engineers and data scientists to support various stages of the machine learning lifecycle. Your day-to-day activities will include:

• Data Preprocessing: Cleaning and preparing data for model training, ensuring data quality and consistency.
• Model Training: Assisting in the training of machine learning models, experimenting with different algorithms and hyperparameters.
• Performance Evaluation: Evaluating model performance using appropriate metrics and techniques, and identifying areas for improvement.
• Pipeline Maintenance: Building and maintaining ML pipelines, ensuring they are scalable and efficient.
• Code Development: Writing and maintaining clean, well-documented code, following best practices for testing and version control.
• Model Monitoring: Monitoring deployed models to ensure they are performing as expected, and assisting in debugging any issues that arise.
• Collaboration: Participating in team meetings, sprint planning, and daily stand-ups to stay aligned with project goals and timelines.

Sprint and Team Collaboration

As part of an agile team, you will participate in sprint planning sessions to define and prioritize tasks for each sprint. You will work on assigned tasks, collaborate with team members to overcome challenges, and provide updates during daily stand-up meetings. At the end of each sprint, you will participate in sprint reviews to demonstrate completed work and gather feedback, as well as sprint retrospectives to discuss what went well and identify areas for improvement. This collaborative environment will provide you with opportunities to learn from experienced team members, contribute to the team's success, and grow your skills as a machine learning engineer.

Qualifications

Qualifications

• Bachelor of Engineering or equivalent
• 3-5 years experience building data products
• Python experience
• Experinece working in cloud environment with one of Databricks, Azure or AWS

Additional Information

Our uniqueness is that we truly celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what truly matters; DEI, work/life balance, development, authenticity, engagement, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's strong people first approach is award winning; Great Place To Work™ in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, color, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Experian Careers - Creating a better tomorrow together

Benefits

Experian care for employee's work life balance, health, safety and wellbeing. In support of this endeavor, we offer best-in-class family well-being benefits, enhanced medical benefits and paid time off.

Experian Careers - Creating a better tomorrow together

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