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- Tasks: Join our data science team to develop AI algorithms and predictive models for diverse industries.
- Company: Dynamic company working with top industrial clients across various sectors.
- Benefits: Competitive salary, flexible benefits, 24/7 GP service, and discounts on retail and gym.
- Why this job: Make a real impact by solving complex problems with cutting-edge data science techniques.
- Qualifications: Experience in Data Science, proficiency in Python, and strong teamwork skills.
- Other info: Great opportunities for learning and career growth in a supportive environment.
The predicted salary is between 28800 - 48000 £ per year.
We are looking for a junior or medior data science engineer to complement our data science team working with many of our industrial customers from various sectors, including (petro-) chemical, paper and pulp, automotive, metallurgy, telecom and food-and beverage.
Responsibilities
- You will typically work together with a more senior member of the team on projects.
- Your day job typically consists of using and extending a broad set of data science and software skills.
- Help build and improve the algorithms in scalable manner for AI-based anomaly detection and predictive modelling.
- Apply and sometimes (co-)invent and implement AI/ML algorithms for processing various types of data (timeseries, tabular etc).
- Development of computer models and doing predictive and prescriptive analytics for various applications.
- Build Proof of Concepts in notebooks, but also integrate these algorithms into the operational flow of the customer, train the users and give support.
- Interface with various data sources over various connector pipelines (SQL, Elasticsearch, Kafka, REST APIs, …).
- Tune algorithms and data pipelines for optimal performance.
- Train, tune and deploy anomaly detection and predictive models on industrial or IoT data.
- Knack/experience of consultancy services.
Qualifications
- Previous hands-on experience in Data Science, delivering machine learning models to production.
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or Engineering – or equivalent.
- Proficiency in Python and relevant data science libraries (NumPy, pandas, scikit-learn etc.).
- Experience with SQL, Power BI, Git & GitHub.
- Strong knowledge of Machine Learning Algorithms and respective theory.
- Ability to work within a team, collaborating effectively with colleagues.
- Strong stakeholder management skills and the ability to influence.
- A drive to learn new technologies and techniques.
- Experience/aptitude towards research and openness to learn new technologies.
- Experience with Azure, Spark (PySpark) Kubeflow – desirable.
Benefits
- We pay competitive salaries based on experience of the candidates, along with this, you will be entitled to an award-winning range of benefits including:
- Access to our company car scheme or car allowance.
- Free confidential 24/7 GP service.
- Hundreds of discounts (including retail, childcare + gym).
- Affordable loans & enhanced pension scheme.
Data Scientist employer: Sneak Peek Tech
Contact Detail:
Sneak Peek Tech Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with data science professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning models and predictive analytics. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data science. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with machine learning models, Python, and any relevant projects you've worked on. We want to see how your skills fit into our team!
Showcase Your Projects: Include examples of your work, especially any Proof of Concepts or algorithms you've developed. This gives us a glimpse into your practical skills and how you approach problem-solving in data science.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for easy reading and make sure to highlight your key achievements. We appreciate straightforward communication!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at Sneak Peek Tech
✨Know Your Algorithms
Brush up on your knowledge of machine learning algorithms and their applications. Be ready to discuss how you've used them in past projects, especially in predictive modelling or anomaly detection. This shows you not only understand the theory but can also apply it practically.
✨Showcase Your Coding Skills
Since proficiency in Python and relevant libraries is key, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice coding challenges that involve data manipulation with NumPy or pandas.
✨Prepare for Team Dynamics
As you'll be working closely with senior team members, think about examples from your past experiences where you've successfully collaborated. Highlight your ability to communicate effectively and manage stakeholder expectations, as this will be crucial in your role.
✨Ask Insightful Questions
At the end of the interview, have a few thoughtful questions ready about the company's data science projects or the technologies they use. This not only shows your interest but also gives you a chance to assess if the company aligns with your career goals.
