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Senior Data Scientist

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 accomplish 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

 

Experian Consumer Services is looking for a Sr. Data Scientist to help create personalized financial solutions for our customers. Your goal will be to extract insights from data and deliver ML projects from beginning to end, including understanding user needs, analyzing data, training/validating ML models, and deploying ML models to applications.

You will:

  • Work with team members to understand desired outcomes and project context.
  • Analyze data to get a full understanding of the information captured data.
  • Discover new data sources and create new input features for analysis.
  • Develop machine learning algorithms with huge data sets to solve challenging business questions.
  • Communicate analytical results to team members.

Qualifications

 

  • Advanced degree in a quantitative field (Machine Learning, Data science, Computer Science) or equivalent professional experience.
  • 5+ years of work experience in a quantitative field such as data science or statistical modeling using cloud computing services such as AWS, Google Cloud Platform, Snowflake, Databricks.
  • Industry experience with statistical modeling techniques such as regression, support vector machines, gradient-boosted trees, and neural nets, including how to optimize models using performance tuning techniques, is required. Experience with deep learning algorithms such as convolutional neural networks and recurrent neural networks.
  • Direct experience with analytical tools and programming languages such as Python or R and SQL.
  • Adopt new languages/tools, write efficient code, and quickly debug. Working knowledge of Tableau. Experience showing analytical results visually in a compelling manner and knowing what type of analysis fits the problem.
  • The ability to extract user requirements from context and conversations. The ability to distill technical knowledge to communicate with a broad audience. The ability to collaborate with others is necessary.
  • • Proactive thinking to identify inefficiencies/roadblocks and brainstorm solutions. Visionary, identifying opportunities to expand the business either from a product or operational perspective.

The benefits and perks are these:

  • Great compensation package and bonus plan
  • Core benefits including full medical, dental, vision, and matching 401K
  • Flexible work environment, ability to work remotely, hybrid or in-office #li-remote
  • Flexible time off, including volunteer time off, vacation, sick, and 12-paid holidays

Additional Information

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 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 an important 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, 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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CEO of Experian
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Average salary estimate

$115000 / YEARLY (est.)
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$100000K
$130000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Scientist, Experian

If you’re ready to take your career to the next level, Experian is excited to invite you as a Senior Data Scientist to join our innovative team working from anywhere in California! At Experian, we’re not just a data and technology company; we’re also passionate about using our analytics to create personalized financial solutions that empower our customers. In this role, you'll dive deep into data, extracting insights that drive machine learning projects from inception to deployment. Collaborating closely with teammates, you’ll develop machine learning algorithms that leverage enormous datasets to tackle complex business challenges. You’ll also have the opportunity to communicate your findings in meaningful ways, translating intricate analytical results into insights that resonate with a broader audience. We’re looking for someone with a strong background in quantitative fields, particularly those skilled in statistical modeling, cloud computing, and analytical programming languages like Python or R. With your proactive mindset and innovative thinking, you’ll help redefine our business approaches while enjoying a flexible work environment that supports work-life balance. Join Experian, where your expertise not only drives our mission but also contributes to our vibrant culture and outstanding workplace ethos. Let's harness the power of data together and create impactful solutions for millions of people around the world!

Frequently Asked Questions (FAQs) for Senior Data Scientist Role at Experian
What responsibilities does a Senior Data Scientist at Experian have?

As a Senior Data Scientist at Experian, you will be responsible for analyzing data to generate insights, developing machine learning algorithms, and translating data-driven results into actionable strategies. Your role includes understanding user needs, collaborating on projects, and communicating findings effectively.

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What qualifications are needed for the Senior Data Scientist position at Experian?

To qualify for the Senior Data Scientist role at Experian, you should have an advanced degree in a quantitative field, with over 5 years of experience in data science or statistical modeling. Proficiency in programming languages like Python or R, and familiarity with cloud services such as AWS is essential.

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How does Experian support the professional development of its Senior Data Scientists?

Experian is committed to employee growth, offering various learning opportunities, mentorship, and resources for development. As a Senior Data Scientist, you will be encouraged to adopt new tools and methodologies while pursuing your career goals in an innovative environment.

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What tools does a Senior Data Scientist at Experian use for data analysis?

Senior Data Scientists at Experian typically use tools such as Python, R, SQL, and Tableau for data analysis. They also utilize cloud platforms like AWS and Google Cloud to manage and analyze vast datasets effectively.

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What can I expect from the work culture at Experian as a Senior Data Scientist?

At Experian, you can expect a supportive and inclusive work culture that values diversity and collaboration. The company prioritizes work-life balance, professional growth, and recognition, making it a great place for you to thrive as a Senior Data Scientist.

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Common Interview Questions for Senior Data Scientist
Can you describe your experience with machine learning algorithms?

When answering this question, provide specific examples of machine learning projects you've worked on, including the algorithms and techniques used. Highlight your problem-solving approach and the impact your solutions had on the business.

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How do you ensure the accuracy of your data analysis?

Explain your methods for validating and testing models, including techniques like cross-validation. Discuss the importance of data quality and how it influences the outcomes of your analytical work.

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What strategies do you use to communicate complex data findings?

Discuss how you tailor your communication style to your audience. Provide examples of visualization tools or techniques you've used to present your findings effectively, ensuring clarity and engagement.

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Can you give an example of a challenging data problem you've solved?

Share a specific challenge you faced in your previous work, how you approached it, the tools and algorithms you utilized, and the successful outcome or learning experience from that project.

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How do you stay current with advancements in data science?

Explain your commitment to continuous learning through online courses, attending workshops, reading relevant literature, or being part of professional organizations. Mention specific resources you find valuable.

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Describe your experience working with cloud computing platforms.

Detail your experience using cloud platforms like AWS or Google Cloud. Discuss how these tools have aided in performing large-scale data analysis and the specific services you've utilized.

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What is your process for feature selection in machine learning?

Outline your approach to feature selection, including the methods you use to assess the significance of features. Provide examples of how this process has improved model performance in past projects.

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How do you handle data privacy and ethical considerations?

Discuss the importance of data privacy and your strategies for ensuring compliance with regulations. Share examples of how you have maintained ethical standards in your data analysis work.

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What programming languages are you proficient in and how do you use them?

List the programming languages you are skilled in, such as Python or R, and describe how you've used them in your work, including specific libraries or frameworks for data analysis and modeling.

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How do you prioritize tasks when working on multiple projects?

Explain your strategies for task management, such as using project management tools, setting clear deadlines, and communicating with stakeholders to ensure successful delivery of your projects.

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We pride ourselves on being certified as a Great Place To Work and firmly believe that creating a positive company culture is less about ping pong tables and more about transparency, connection, and "work with purpose." The unique perspective of e...

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Full-time, remote
DATE POSTED
March 25, 2025

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