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- Tasks: Analyse complex datasets, develop predictive models, and support decision-making.
- Company: Join a dynamic company in Maidenhead with a focus on data-driven solutions.
- Benefits: Enjoy hybrid work with 3 days onsite and 2 days remote, plus opportunities for growth.
- Why this job: Be part of a collaborative team that values innovation and mentorship in data science.
- Qualifications: Bachelor’s degree in a related field and 2+ years of experience in data science required.
- Other info: Proficiency in Python or R and experience with SQL are preferred.
The predicted salary is between 28800 - 48000 £ per year.
I am looking for a Data Engineer / Data Scientist for a company in the Maidenhead area. Work is Hybrid – 3 days onsite, 2 days remote. You will be leveraging your analytical skills and programming experience to extract insights from complex datasets, develop predictive models and support decision making.
KEY RESPONSIBILITIES
- Data Analysis & Modelling: Analyse large, complex datasets to identify trends, patterns, and actionable insights. Develop, implement, and optimize machine learning models to solve business problems. Conduct A/B testing and experimental analysis to validate hypotheses.
- Data Management & Engineering: Collaborate with data engineering teams to ensure data quality, accessibility, and efficiency. Design and develop ETL pipelines and workflows for data preprocessing. Develop automated tests to validate the processes and models you create.
- Collaboration & Communication: Collaborate with stakeholders to define project goals, requirements, and deliverables. Actively participate in design meetings to help shape the solutions that the team delivers. Present findings and recommendations to technical and non-technical audiences. Acquire domain knowledge to inform modelling opportunities and model feature creation.
- Technical Leadership: Mentor junior data scientists and provide peer reviews for modelling projects. Stay current with industry trends, tools, and best practices to continuously improve the team's capabilities.
QUALIFICATIONS
- Education: Bachelor’s degree in data science, Statistics, Mathematics, or a related field.
- Experience: 2 or more years of experience in a data science or analytics role. Proven experience in building machine learning models, statistical analysis, and predictive analytics. Experience designing experiments or modelling approaches to solve a specified business problem.
PREFERRED QUALIFICATIONS
- Proficiency in programming languages such as Python or R; knowledge of R is an advantage.
- Experience with SQL and working knowledge of relational databases.
- Proficiency with data visualisation tools and techniques.
- Experience with AWS is a plus.
- Strong problem-solving and critical-thinking abilities.
- Excellent communication and presentation skills.
- Ability to manage multiple projects and prioritize tasks effectively.
Data Scientist employer: WHD
Contact Detail:
WHD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, R, SQL, and AWS. Having hands-on experience or projects showcasing your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Engage with the data science community by attending meetups, webinars, or online forums. Networking with professionals in the field can provide insights into industry trends and may even lead to referrals for job openings.
✨Tip Number 3
Prepare to discuss your past projects in detail during interviews. Be ready to explain your thought process, the challenges you faced, and how you overcame them, especially in relation to data analysis and machine learning models.
✨Tip Number 4
Showcase your communication skills by practising how to present complex data findings to non-technical audiences. Being able to convey your insights clearly will demonstrate your ability to collaborate effectively with stakeholders.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and engineering. Focus on your analytical skills, programming experience, and any specific projects that demonstrate your ability to work with complex datasets.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your understanding of the role. Mention specific experiences where you've developed machine learning models or conducted data analysis, and explain how these relate to the company's needs.
Showcase Technical Skills: In your application, clearly list your proficiency in programming languages like Python or R, as well as your experience with SQL and data visualisation tools. Providing examples of how you've used these skills in past roles can strengthen your application.
Highlight Collaboration Experience: Since the role involves collaboration with stakeholders, emphasise any previous experience working in teams or mentoring others. Discuss how you’ve communicated complex data insights to both technical and non-technical audiences.
How to prepare for a job interview at WHD
✨Showcase Your Analytical Skills
Be prepared to discuss specific examples of how you've analysed complex datasets in the past. Highlight any trends or insights you discovered and how they impacted decision-making.
✨Demonstrate Your Technical Proficiency
Make sure to brush up on your programming skills, especially in Python or R. Be ready to talk about your experience with machine learning models and any relevant projects you've worked on.
✨Prepare for Collaboration Questions
Since collaboration is key in this role, think of examples where you've worked with stakeholders or cross-functional teams. Be ready to explain how you defined project goals and delivered results.
✨Communicate Clearly and Effectively
Practice explaining complex technical concepts in simple terms. You may need to present findings to non-technical audiences, so clarity and confidence in your communication are essential.
