At a Glance
- Tasks: Lead client projects, solve complex data problems, and present insights clearly.
- Company: Join Daintta, a dynamic company solving tough data challenges for clients across the UK.
- Benefits: Enjoy hybrid working, fair rewards, and opportunities for personal growth in a fast-paced environment.
- Why this job: Be part of an innovative team where your voice matters and you can shape the future.
- Qualifications: 5+ years in data science, experience with cloud infrastructure, and strong interpersonal skills required.
- Other info: Must be eligible for SC clearance; British citizenship and 5 years residency in the UK needed.
The predicted salary is between 43200 - 72000 £ per year.
Data Scientist
Who are we looking for?
You enjoy working on complex data problems whilst being able to suggest simple (yet effective) solutions. You are comfortable working with uncertainty and like to make things clearer. You’re passionate about technology and keep up as it evolves. You focus on the future and thrive most when solving problems. Client’s love working with you. You are honest and do things when you say you will, you also know how to explain things clearly and concisely. You can educate and inspire. You’ve got a background in data science, machine learning algorithms, data analytics, and data engineering along with their technologies. You’re equally comfortable presenting to clients, providing advice or building prototypes. You’re a collaborator and enjoy stepping out of your role from time to time, whether it’s to support your clients, colleagues or to learn something new.
Key Responsibilities
- Leading client projects and providing subject matter expertise.
- Working in scrum-like environments for iterative and ‘fail-fast’ work and innovation.
- Working in cross-disciplinary teams.
- Working at the PoC (proof-of-concept) stage through to MVP and MMP stages.
- Assessing your clients’ business and technical needs with the ability to identify opportunities for data science to be used. Managing client and stakeholder relationships appropriately.
- Solving problems using data science techniques and in a scientifically robust fashion.
- Identifying data sources that are relevant to client needs, and related data science concepts that leverage those sources to aid the client.
- Working with various forms of data (e.g., unstructured, semi-structured or structured; text, time-series or image) and suitably modelling them (e.g., table, key-value pair, graph) for efficient data science use.
- Investigating and analysing data to see ‘the wood from the trees’ and drilling down to the ‘whys’ of the data.
- Applying statistical and evidence-based techniques to inform insights and actions from the data.
- Communicating technical content at the right pitch/level both internally and to customers.
- Presenting to the client, using data science tooling and investigation, a ‘story’ of the data.
- Building maintainable code that use existing data science libraries, implement existing data science techniques, or implement novel techniques.
- Designing, evaluating, and implementing on-premise, cloud-based and hybrid data science and machine learning techniques and algorithms (including providing relevant review and guidance on testing aspects, identification of risks and proposing and implementing their mitigations).
- Developing scalable models and algorithms that can be deployed into production environments.
- Applying ethical principles in handling data.
- Accurately delivering high quality work to agreed timelines and taking the initiative and knowing how to jump straight in.
- Supporting client engagements, including pitches and presentations.
- Helping to support & grow Daintta by actively inputting into the company strategy and helping to shape our future.
- Representing us and our core values: transparent, fair and daring
Sounds like something you’d enjoy? Here’s a bit more about you
- You have 5+ years of degree level industry experience in data science.
- You have extensive degree level experience in a STEM subject.
- You have experience of working in a consultancy, engineering, or data industry.
- You have led client delivery across a range of projects, e.g., data science, data analytics, data engineering, data intelligence, data security and proven experience in relevant technologies (e.g., Python applied to data science), as an individual-contributor and leading a small team.
- You have experience working on cloud-based infrastructure (e.g., AWS, Azure, GCP).
- You have demonstrable continuous personal development.
- You have strong interpersonal skills.
- You have experience with using CI/CD tooling to analyse, build, test and deploy your code and proven experience in their technologies.
- You have experience in database technologies (e.g., SQL, NoSQL such as Elasticsearch and Graph databases).
- You have a good understanding of coding best practices and design patterns and experience with code and data versioning, dependency management, code quality and optimisation, error handling, logging, monitoring, validation and alerting.
Location
Hybrid, with 2-3 days working from Daintta office (London or Cheltenham) or on client site as required.
What’s in for you
In addition to being rewarded fairly for your contribution to the business, you get to work in a dynamic organisation that is agile and responsive. A business that is growing fast and where you get to drive and shape the future. A place where you are respected by everyone and your voice is important. Somewhere where you can be innovative and creative. A place where you have the opportunity to learn about all aspects of business from marketing to sales, to delivery and business operations.
Time to tell you about us!
We are Daintta. We provide deep expertise with technical and business specialists to help clients and organisations secure and protect the UK. In complex environments, we use innovative methods to solve the hardest data challenges to help organisations make more informed and accurate decisions, at scale and faster. We are agile, responsive, independent, and collaborative while our values of Fair, Transparent and Daring guide all our decision making.
Security Information
Due to the nature of this position, you must be willing and eligible to achieve a minimum of SC clearance. To qualify, you must be a British Citizen and have resided in the UK for the last 5 years. For more information about clearance eligibility, please see https://www.gov.uk/government/organisations/united-kingdom-security-vetting
Seniority level
- Mid-Senior level
Employment type
- Full-time
Job function
- Information Technology and Consulting
Industries
- IT Services and IT Consulting
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Data Scientist employer: Daintta
Contact Detail:
Daintta Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest data science tools and technologies, especially those mentioned in the job description like Python, AWS, and CI/CD tooling. Being able to discuss your hands-on experience with these tools during interviews will demonstrate your technical proficiency.
✨Tip Number 2
Prepare to showcase your problem-solving skills by thinking of specific examples where you've tackled complex data challenges. Be ready to explain your thought process and the impact of your solutions on previous projects, as this aligns with what clients appreciate.
✨Tip Number 3
Brush up on your communication skills, particularly how to present technical content to non-technical stakeholders. Practice explaining complex concepts in simple terms, as this is crucial for building client relationships and ensuring they understand your insights.
✨Tip Number 4
Network with professionals in the data science field, especially those who have experience in consultancy or similar roles. Engaging with industry peers can provide valuable insights and potentially lead to referrals, increasing your chances of landing the job with us.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science, machine learning, and data engineering. Use specific examples that demonstrate your problem-solving skills and ability to work with various data types.
Craft a Compelling Cover Letter: In your cover letter, express your passion for technology and how you keep up with industry trends. Mention your collaborative nature and provide examples of how you've successfully led client projects or worked in scrum-like environments.
Showcase Your Technical Skills: Clearly outline your technical skills relevant to the role, such as proficiency in Python, experience with cloud-based infrastructure, and familiarity with CI/CD tooling. Be specific about the technologies you've used and the outcomes achieved.
Demonstrate Your Communication Skills: Since the role involves presenting to clients and explaining complex concepts, include examples in your application that showcase your ability to communicate technical content clearly and concisely. This could be through past presentations or written reports.
How to prepare for a job interview at Daintta
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples of complex data problems you've solved in the past. Highlight your thought process and the effective solutions you implemented, as this aligns with what the company values.
✨Communicate Clearly and Concisely
Practice explaining technical concepts in simple terms. The ability to communicate effectively with clients and colleagues is crucial, so be ready to demonstrate how you can make complex ideas accessible.
✨Demonstrate Your Passion for Technology
Stay updated on the latest trends in data science and machine learning. Be prepared to discuss recent advancements or tools you've explored, showing your enthusiasm for continuous learning and innovation.
✨Emphasise Collaboration and Flexibility
Share experiences where you've worked collaboratively across teams or stepped outside your role to support others. This will showcase your adaptability and willingness to contribute to the company's success.