At a Glance
- Tasks: Teach data skills through engaging workshops and support apprentices in their learning journey.
- Company: Join a forward-thinking organisation dedicated to diversity and inclusion.
- Benefits: Enjoy 27 days holiday, private medical insurance, and a flexible hybrid working model.
- Other info: Dynamic role with opportunities for continuous professional development and a vibrant learning environment.
- Why this job: Make a real difference by empowering the next generation of data professionals.
- Qualifications: Strong communication skills, proficiency in SQL and data visualisation tools like Tableau.
The predicted salary is between 40000 - 40000 £ per year.
Salary: £40,000 - 40,000 per year
Requirements
- Strong written, on‑camera communication, and presentation skills.
- Ability to adapt communication to explain complex concepts to both technical and non‑technical stakeholders.
- Strong critical thinking and problem‑solving skills, especially in an online classroom setting.
- Commitment to continuous professional development and staying current with industry trends.
- Proficiency in at least two of the following: Excel for BI, Tableau, and Power BI.
- Strong SQL skills and ideally Python, demonstrated through real‑world projects.
- Practical knowledge of predictive modelling, such as regression and decision trees, and time‑series forecasting, such as SARIMA.
- Solid understanding of statistical methods and their applications.
- Proven experience applying data and advanced analytics in professional settings.
- Strong commitment to ethical and responsible data use, with hands‑on experience in data governance and knowledge of data protection laws.
- Full‑time, permanent commitment to join our team.
Responsibilities
- Deliver technical learning content through workshops and drop‑in sessions.
- Support apprentices in upskilling across AI and Data technical areas.
- Help apprentices develop the Knowledge, Skills, and Behaviours required throughout their programme.
- Facilitate delivery sessions confidently and ensure sessions meet learning objectives within the allotted time.
- Adhere to our Coach Quality framework to deliver a consistent experience for every apprentice.
- Create a vibrant, inclusive, and motivating learning environment that drives engagement and satisfaction.
- Moderate assignments in line with mark schemes and provide clear feedback and feed‑forward to support ongoing development.
- Maintain an owners mentality by taking initiative, sharing feedback, and supporting learner progress and success.
- Liaise regularly with coaches to align on apprentice interventions and completion of programme.
- Coordinate with cohort coaches and operations members on apprentice development and progress.
- Use resources and learning opportunities to stay current on knowledge, learning, and product updates.
- Build and maintain credibility with apprentices through professional experience, domain knowledge, and client context.
- Create a compelling narrative about our mission and offering, helping apprentices connect with our purpose throughout their apprenticeship and beyond.
Technologies
- AI
- Excel
- Support
- Power BI
- Python
- SQL
- Tableau
Benefits
- 27 days holiday plus additional wellbeing and volunteer days.
- Private medical insurance.
- A cashback scheme.
- Life insurance.
- Gym and wellness resources.
- Mental health support.
- A hybrid working model.
- A work‑from‑anywhere scheme for up to 10 days per year.
We are committed to diversity, equity, inclusion, and safeguarding, and successful applicants will need to complete DBS checks depending on the role.
Data Instructor employer: Sivara GmbH
As a Data Instructor, you will thrive in a dynamic and inclusive work environment that prioritises professional growth and continuous learning. With a strong commitment to employee wellbeing, we offer generous benefits including 27 days of holiday, private medical insurance, and a hybrid working model, allowing you to balance your personal and professional life effectively. Join us to make a meaningful impact on apprentices' journeys while being part of a forward-thinking team dedicated to ethical data practices and innovative teaching methods.
StudySmarter Expert Advice🤫
We think this is how you could land Data Instructor
✨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 Sivara GmbH!
✨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 Instructor at Sivara GmbH.
✨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 Sivara GmbH.
✨Apply Directly through Our Website
When you find a suitable opening like Data Instructor at Sivara GmbH, 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 Instructor
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 Sivara GmbH, 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 Sivara GmbH. 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 Sivara GmbH
✨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 Sivara GmbH!
✨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.
