AI Consultant

Equifax, Inc.
London
4 days ago
Create job alert

OurAI Consultantroles 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. Want to know more?

What You’ll Do:

  1. Conduct in-depth analysis of data available to Equifax and its partners.

  2. Collaborate with product managers to conduct market research and validate product needs.

  3. Develop and test AI models and algorithms, utilizing platforms like Vertex AI and BQML.

  4. Contribute to the creation of business cases for proposed AI solutions.

  5. Evaluate the feasibility and potential impact of AI projects.

  6. Provide technical guidance and support to junior analysts.

  7. Be proficient in Python, stay up-to-date on the latest advancements in AI and machine learning.

  8. Utilize combined knowledge of data structures, analytics, algorithms/models, and strong computer science fundamentals to independently prepare datasets, conduct analytics, and develop deployable solutions.

  9. Collect, analyze and interpret large data assets to define and build multiple innovative solution components leveraging business and technical expertise. Support the analytical strategy by understanding critical technical capabilities and suggesting opportunities.

  10. Lead the development of projects with multiple deliverables, leveraging business and technical expertise.

  11. 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., encouraging enhanced solutions.

  12. Package, summarize, visualize, and perform storytelling on analytical findings and results for management and business users.

  13. Communicate results to external stakeholders and mid-level leadership, able to communicate the business impact of work.

  14. Evaluate the technical work of peers and junior data scientists, guiding them on deliverable quality and accuracy.


What experience you need:

  1. Bachelor's degree (2:1 or above) in a numerical subject (Computer Science, Mathematics, Statistics, Physics, Engineering).

  2. Solid experience in data analysis, machine learning, and AI development.

  3. Hands-on experience with cloud-based AI platforms and tools.

  4. Proficiency in programming languages such as Python and SQL.

  5. Strong analytical and problem-solving skills.

  6. Ability to work independently and as part of a team.

  7. Good communication, presentation, and visualization skills.

  8. Strong experience in a related analytical role.

  9. Proven track record of designing and developing predictive models in real-world applications.

  10. Experience with model performance evaluation and predictive model optimization for accuracy and efficiency.

  11. Cloud certification strongly preferred.

  12. Additional role-based certifications may be required depending upon region/BU requirements.


What could set you apart:

  1. Experience with specific AI techniques, such as neural networks or natural language processing.

  2. Knowledge of the financial services industry.

  3. Contributions to open-source AI projects.

  4. Experience with data visualization tools.

  5. Passion for data science, data mining, machine learning, and experience with big data architectures and methods.

  6. A Master's degree in a quantitative field (Statistics, Mathematics, Economics).

#J-18808-Ljbffr

Related Jobs

View all jobs

AI Consultant

AI Consultant

AI Consultant

AI Consultant

AI Consultant

AI Consultant

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.