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- Tasks: Analyze data, develop AI models, and collaborate with teams to create innovative solutions.
- Company: Equifax empowers you to reach your potential and make a meaningful impact.
- Benefits: Enjoy flexible benefits, 26 days holiday, and personal development opportunities.
- Why this job: Join a dynamic team pushing the boundaries of AI and big data in a supportive culture.
- Qualifications: Bachelor's degree in a numerical subject and solid experience in data analysis and AI development.
- Other info: Cloud certification preferred; passion for data science is a plus!
The predicted salary is between 43200 - 72000 £ per year.
Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you.
Our AI Consultant roles are unique. The ideal candidate is a rare hybrid, a scientist with strong technical skills in AI and machine learning, the programming abilities to scrape, combine, and manage data from a variety of sources, and a statistician who knows how to derive insights from the information within. They will combine the skills to create new prototypes with the creativity and thoroughness to ask and answer the deepest questions about the data, what secrets it holds, and to push the boundaries of what is possible with big data.
What You’ll Do:
- Conduct in-depth analysis of data available to Equifax and its partners.
- Collaborate with product managers to conduct market research and validate product needs.
- Develop and test AI models and algorithms, utilizing platforms like Vertex AI and BQML.
- Contribute to the creation of business cases for proposed AI solutions.
- Evaluate the feasibility and potential impact of AI projects.
- Provide technical guidance and support to junior analysts.
- Be proficient in Python, stay up-to-date on the latest advancements in AI and machine learning.
- Utilize combined knowledge of data structures, analytics, algorithms/models, and strong computer science fundamentals to independently prepare datasets, conduct analytics, and develop deployable solutions.
- Collect, analyze and interpret large data assets to define and build multiple innovative solution components leveraging business and technical expertise.
- Lead the development or projects with multiple deliverables, leveraging business and technical expertise.
- Work on high-complexity tasks in problems often within multiple business or analytical domains, collaborating with other teams to develop predictive models, risk assessments, fraud detection, recommendation engines, etc.
- Package, summarize, visualize and perform storytelling on analytical findings and results for management and business users.
- Communicate results to external stakeholders and mid-level leadership, able to communicate business impact of work.
- Evaluate the technical work of peer and junior data scientists, guiding them on deliverable quality and accuracy.
What experience you need:
- Bachelor’s degree (2:1 or above) in a numerical subject (Computer Science, Mathematics, Statistics, Physics, Engineering).
- Solid experience in data analysis, machine learning, and AI development.
- Hands-on experience with cloud-based AI platforms and tools.
- Proficiency in programming languages such as Python and SQL.
- Strong analytical and problem-solving skills.
- Ability to work independently and as part of a team.
- Good communication and presentation and visualization skills.
- Strong experience in a related analytical role.
- Proven track record of designing and developing predictive models in real-world applications.
- Experience with model performance evaluation and predictive model optimization for accuracy and efficiency.
- Cloud certification strongly preferred.
- Additional role-based certifications may be required depending upon region/BU requirements.
What could set you apart:
- Experience with specific AI techniques, such as neural networks or natural language processing.
- Knowledge of the financial services industry.
- Contributions to open-source AI projects.
- Experience with data visualization tools.
- Passion for data science, data mining, machine learning, and experience with big data architectures and methods.
- A Master’s degree in a quantitative field (Statistics, Mathematics, Economics).
The Perks of being an Equifax Employee:
We offer a wide range of company-supported benefits including contributory pension, life cover, income protection, healthcare, enhanced maternity and sick pay, 26 days holiday and a day off for your birthday, with the ability to buy and sell and free credit checks. We also offer flexible benefits ranging from cycle to work, discounted travel options, gym membership, dining and leisure discounts, financial & savings plans, mobile discounts plus much more!
We also support personal development and have a range of learning options including our global online learning platform and allow you to bring your whole self to work supported by our Inclusion and Diversity, Wellbeing and Employee Engagement forums.
Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference!
Primary Location: GBR-London GBR-Leeds-6-Wellington, GBR-Nottingham
Function: Function – Data and Analytics
Schedule: Full time
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AI Senior Analyst employer: Kount
Contact Detail:
Kount Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Senior Analyst
✨Tip Number 1
Make sure to showcase your hands-on experience with cloud-based AI platforms like Vertex AI and BQML. Highlight any projects where you've developed or tested AI models, as this will demonstrate your practical skills in the field.
✨Tip Number 2
Emphasize your proficiency in Python and SQL, as these programming languages are crucial for the role. Consider sharing specific examples of how you've used them to solve complex data problems or develop predictive models.
✨Tip Number 3
Show your passion for AI and machine learning by discussing any contributions you've made to open-source projects or any innovative solutions you've developed. This can set you apart from other candidates and demonstrate your commitment to the field.
✨Tip Number 4
Prepare to discuss your experience with model performance evaluation and optimization. Be ready to explain how you've improved the accuracy and efficiency of predictive models in real-world applications, as this is a key aspect of the role.
We think you need these skills to ace AI Senior Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data analysis, machine learning, and AI development. Emphasize your proficiency in Python and SQL, as well as any hands-on experience with cloud-based AI platforms.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how your skills align with the role. Mention specific AI techniques you are familiar with, such as neural networks or natural language processing, and how they can benefit Equifax.
Showcase Relevant Projects: Include examples of projects where you designed and developed predictive models. Highlight your contributions to open-source AI projects or any experience with data visualization tools to set yourself apart.
Prepare for Technical Questions: Be ready to discuss your analytical and problem-solving skills during the interview. Prepare to explain your approach to model performance evaluation and optimization, as well as your experience with big data architectures.
How to prepare for a job interview at Kount
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AI and machine learning, particularly your proficiency in Python and SQL. Highlight specific projects where you've developed or tested AI models, and be ready to explain the algorithms you used.
✨Demonstrate Analytical Thinking
During the interview, emphasize your problem-solving skills by discussing how you've approached complex data analysis tasks in the past. Use examples that showcase your ability to derive insights from large datasets and how those insights impacted business decisions.
✨Communicate Effectively
Since the role involves communicating results to stakeholders, practice summarizing your analytical findings clearly and concisely. Be ready to explain the business impact of your work and how you can visualize data to tell a compelling story.
✨Stay Updated on Industry Trends
Show your passion for AI and machine learning by discussing recent advancements in the field. Mention any relevant certifications or contributions to open-source projects, as this demonstrates your commitment to continuous learning and staying at the forefront of technology.
