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For Companies At a Glance
- Tasks: Dive deep into data analysis and develop cutting-edge AI models.
- Company: Join Equifax, a leader in data analytics and AI solutions.
- Benefits: Enjoy flexible work options, competitive pay, and opportunities for growth.
- Why this job: Be at the forefront of AI innovation and make a real impact with your skills.
- Qualifications: Bachelor's degree in a numerical subject and solid experience in AI and machine learning required.
- Other info: Cloud certification preferred; passion for data science is a plus!
The predicted salary is between 43200 - 72000 £ per year.
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.
- Support the analytical strategy by understanding critical technical capabilities and suggesting opportunities.
- Lead the development of 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., encouraging enhanced solutions.
- 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 the business impact of work.
- Evaluate the technical work of peers 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, 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).
AI Consultant employer: Equifax, Inc.
Contact Detail:
Equifax, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Consultant
✨Tip Number 1
Familiarise yourself with the latest AI and machine learning trends. Follow industry leaders on social media, read relevant blogs, and participate in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Build a portfolio showcasing your projects related to AI and data analysis. Include examples of predictive models you've developed, particularly those that have real-world applications. This tangible evidence of your skills can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the AI and data science community. Attend meetups, webinars, or conferences to connect with others in the field. These connections can lead to valuable insights and potential job referrals.
✨Tip Number 4
Prepare to discuss your problem-solving approach in detail. Be ready to explain how you've tackled complex analytical challenges in the past, as this role requires strong analytical and problem-solving skills. Use specific examples to illustrate your thought process.
We think you need these skills to ace AI Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI, machine learning, and data analysis. Emphasise your programming skills in Python and SQL, as well as any relevant projects or contributions to open-source AI initiatives.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how your unique skill set aligns with the role of an AI Consultant. Mention specific experiences that demonstrate your ability to conduct in-depth data analysis and develop AI models.
Showcase Relevant Projects: Include examples of past projects where you developed predictive models or worked with cloud-based AI platforms. Highlight your problem-solving skills and any innovative solutions you created using big data.
Prepare for Technical Questions: Anticipate technical questions related to AI techniques, model performance evaluation, and data visualisation. Be ready to discuss your analytical approach and how you communicate results to stakeholders.
How to prepare for a job interview at Equifax, Inc.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AI and machine learning in detail. Highlight specific projects where you've developed models or algorithms, and be ready to explain the technical challenges you faced and how you overcame them.
✨Demonstrate Data Storytelling
Since the role involves communicating analytical findings, practice summarising complex data insights into clear, impactful narratives. Use examples from your past work to illustrate how you've effectively communicated results to stakeholders.
✨Prepare for Problem-Solving Questions
Expect to tackle real-world problems during the interview. Brush up on your analytical and problem-solving skills, and be ready to walk through your thought process when approaching a complex data challenge.
✨Stay Updated on AI Trends
The field of AI is constantly evolving, so demonstrate your passion by discussing recent advancements or trends in AI and machine learning. This shows that you're not only knowledgeable but also genuinely interested in the field.
