At a Glance
- Tasks: Lead the personalization strategy and drive data usage independently.
- Company: Join a forward-thinking client building a new personalization team.
- Benefits: Autonomy in your role, competitive salary, and opportunities for growth.
- Other info: Dynamic environment with a focus on innovation and collaboration.
- Why this job: Make a real impact by shaping the future of data-driven personalization.
- Qualifications: Strong experience in data science, AWS, SQL, and leadership skills.
The predicted salary is between 60000 - 80000 £ per year.
Our client is standing up a brand-new personalization team and needs a senior consultant to join immediately. The successful candidate must independently define how data is used, set and drive personalization strategy, and be willing to push the team's existing direction.
Working Style & Fit
- This role is defined by autonomy, not oversight.
- The client is looking for someone who:
- Sets their own direction rather than waiting to be told what to do
- Pushed the team forward technically and strategically, without hand-holding
- Is comfortable being the senior voice in the room from day one
- Can work productively with strong technical stakeholders - candidates who clash with or repeatedly ignore direction from senior architects will not last, regardless of technical strength
What You'll Deliver
- An assessment of current personalization data usage and a clear point of view on strategy
- Hands-on database builds and pipeline work in AWS
- Software development contributions alongside the core data work
- Independent leadership of the personalization roadmap
- Ongoing technical direction for the existing team
Requirements
- Strong personalization experience
- Proven track record moving fluidly between data science and hands-on software engineering
- AWS and SQL, with confirmed experience building databases in AWS
- A genuine self-starter with a demonstrable history of setting direction independently
- Track record of constructively challenging technical direction and raising a team's standard
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨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 Gravitas Group!
✨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 Data Scientist at Gravitas Group.
✨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 Gravitas Group.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist at Gravitas Group, 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 Data Scientist
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 Gravitas Group, 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 Gravitas Group. 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 Gravitas Group
✨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 Gravitas Group!
✨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.
