AI & Data Transformation Lead – Hybrid (London)

AI & Data Transformation Lead – Hybrid (London)

London Full-Time 70000 - 90000 Β£ / year (est.) Home office (partial)
Jefferson Frank

At a Glance

  • Tasks: Lead exciting AI and data transformation projects while engaging with senior stakeholders.
  • Company: Join a forward-thinking company in the heart of London with a hybrid work model.
  • Benefits: Enjoy competitive pay, flexible working, and opportunities for professional growth.
  • Other info: Fast-paced environment with a focus on innovation and career advancement.
  • Why this job: Make a real impact by shaping modern data platforms and strategies.
  • Qualifications: Experience in data delivery and strong collaboration skills are essential.

The predicted salary is between 70000 - 90000 Β£ per year.

Jefferson Frank is seeking a Data & AI Delivery Specialist in London with a hybrid work arrangement.

The role focuses on delivering large-scale Data, Analytics and AI transformation projects, engaging senior stakeholders, and translating business needs into modern data platforms and roadmaps.

You will work with Azure, AWS or GCP, develop data strategies and governance, and collaborate with Architects, Data Scientists and Analysts in a fast-paced environment.

#J-18808-Ljbffr

AI & Data Transformation Lead – Hybrid (London) employer: Jefferson Frank

Join a leading UK manufacturing and supply-chain organisation that is at the forefront of digital transformation. With a strong commitment to employee development, you will have access to competitive salaries and opportunities to enhance your IT and Data management skills in a collaborative and dynamic work environment. Located in Surrey, this hybrid role offers the chance to engage with diverse stakeholders while contributing to innovative solutions that drive business success.

Jefferson Frank

Contact Details:

Jefferson Frank Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land AI & Data Transformation Lead – Hybrid (London)

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Jefferson Frank!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI & Data Transformation Lead – Hybrid (London) at Jefferson Frank.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Jefferson Frank.

✨Apply Directly through Our Website

When you find a suitable opening like AI & Data Transformation Lead – Hybrid (London) at Jefferson Frank, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace AI & Data Transformation Lead – Hybrid (London)

Data Transformation
AI Delivery
Stakeholder Engagement
Business Needs Analysis
Modern Data Platforms
Data Strategies
Data Governance

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 Jefferson Frank, 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 Jefferson Frank. 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 Jefferson Frank

✨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 Jefferson Frank!

✨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.