At a Glance
- Tasks: Analyse data, develop AI models, and collaborate on innovative solutions.
- Company: Join Equifax, a leader in data analytics and AI solutions.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Dynamic role with opportunities to lead projects and mentor junior analysts.
- Why this job: Make an impact in AI while working with cutting-edge technology and talented teams.
- Qualifications: Bachelor's degree in a numerical subject and experience in AI development.
The predicted salary is between 36000 - 60000 £ per year.
Overview
In this AI Consultant role, you will analyze large data assets, develop and validate AI models, and translate insights into business impact at Equifax. You’ll collaborate with product managers to define needs and build compelling business cases for AI solutions. You’ll apply Python, SQL, and cloud AI tools to create deployable data-driven solutions and guide junior analysts. This hybrid position blends data science, statistics, and software fundamentals to push the boundaries of what data can reveal. You’ll work in a fast-moving, cross-functional environment to shape AI strategy.
Pay / Benefits
- contributory pension
- life cover
- healthcare
- 26 days holiday
- birthday day off
- flexible benefits
Responsibilities
- Conduct in-depth data analysis for Equifax and partners
- Collaborate with product managers for market research and validation of needs
- Develop and test AI models and algorithms using platforms like Vertex AI and BQML
- Create business cases and assess AI project feasibility and impact
- Provide technical guidance to junior analysts
- Independently prepare datasets and develop deployable solutions
- Lead projects with multiple deliverables leveraging business and technical expertise
- Communicate results to management and external stakeholders
- Evaluate peer work and ensure deliverable quality and accuracy
- Package and visualize analytical findings for business users
Key requirements
- Bachelor's degree in a numerical subject
- Solid experience in data analysis, ML, and AI development
- Hands-on experience with cloud-based AI platforms and tools
- Proficiency in Python and SQL
- Strong analytical and problem-solving skills
- Ability to work independently and in a team
- Good communication, presentation, and visualization skills
- Proven track record designing and deploying predictive models
- Experience with model evaluation and optimization
- Cloud certification strongly preferred
- strong communication and presentation abilities
- team collaboration and mentoring
- problem-solving mindset
- Python
- SQL
- Vertex AI
AI Consultant in London employer: Equifax
Equifax is an exceptional employer that fosters a dynamic work culture in Greater London, where innovation and collaboration thrive. Employees benefit from comprehensive growth opportunities, competitive compensation, and the chance to make a meaningful impact on the company's revenue strategy through strategic partnerships. Join us to be part of a forward-thinking team dedicated to driving success and expanding market reach.
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We think this is how you could land AI Consultant in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace AI Consultant in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Equifax, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Equifax. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Equifax
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Equifax!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
