Hands-On Data Science Lead - Hybrid | Bonus Eligible in Basingstoke

Hands-On Data Science Lead - Hybrid | Bonus Eligible in Basingstoke

Basingstoke Full-Time 59400 - 72600 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead data science projects, manage predictive models, and drive strategic initiatives.
  • Company: Join ShareForce, a forward-thinking company focused on data-driven solutions.
  • Benefits: Enjoy a hybrid work model, bonus eligibility, and opportunities for professional growth.
  • Other info: Collaborate with external partners and ensure robust governance in data delivery.
  • Why this job: Shape data strategies and make a real impact in a dynamic environment.
  • Qualifications: Experience in data science and strong leadership skills required.

The predicted salary is between 59400 - 72600 £ per year.

Share Force invites a hands-on Data Science Lead to own four predictive models, guiding governance and the internal data science function.

You will shape data strategies in a Microsoft Azure and Databricks environment, advise senior stakeholders, and translate complex analytics into commercial value.

You will manage model lifecycle, drive strategic initiatives, and work with external partners to embed capability within the team, ensuring robust governance and scalable delivery.

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Hands-On Data Science Lead - Hybrid | Bonus Eligible in Basingstoke employer: Shareforce

Shareforce is an exceptional employer that fosters a dynamic and collaborative work environment in the heart of Oxford. With a strong focus on employee growth, we offer unique opportunities for professional development alongside hands-on experience in scientific operations. Our commitment to innovation and teamwork ensures that every team member plays a vital role in our mission to advance scientific solutions.

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Contact Details:

Shareforce Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Hands-On Data Science Lead - Hybrid | Bonus Eligible in Basingstoke

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 Shareforce!

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 Hands-On Data Science Lead - Hybrid | Bonus Eligible at Shareforce.

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 Shareforce.

Apply Directly through Our Website

When you find a suitable opening like Hands-On Data Science Lead - Hybrid | Bonus Eligible at Shareforce, 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 Hands-On Data Science Lead - Hybrid | Bonus Eligible in Basingstoke

Predictive Modelling
Data Strategy Development
Microsoft Azure
Databricks
Stakeholder Management
Analytics Translation
Model Lifecycle Management

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 Shareforce, 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 Shareforce. 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 Shareforce

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 Shareforce!

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.