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- Tasks: Join our data science team to build AI algorithms and predictive models for diverse industries.
- Company: We partner with industrial clients across sectors like automotive, telecom, and food-and-beverage.
- Benefits: Enjoy competitive salaries, a company car scheme, 24/7 GP service, and hundreds of discounts.
- Why this job: Gain hands-on experience with cutting-edge technologies while making an impact in various domains.
- Qualifications: Bachelor's or Master's in Data Science or related field; proficiency in Python and machine learning.
- Other info: Ideal for those eager to learn and grow in a collaborative 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.
You will use various ML / AI / data science libraries and work on a variety of applications.
You will get to use various state of the art technologies including Elastic, Kafka, Kubernetes and Luigi.
Finally, you will have the opportunity to look behind the scenes of many domains and data.
What are your responsibilities?
You will typically work together with a more senior member of the team on projects and your day job typically consists of:
- Help build and improve the algorithms in a 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.).
- Develop computer models and perform predictive and prescriptive analytics for various applications.
- Build Proof of Concepts in notebooks, integrate these algorithms into the operational flow of the customer, train the users, and provide support.
- Interface with various data sources over various connector pipelines (SQL, Elasticsearch, Kafka, REST APIs, etc.).
- Tune algorithms and data pipelines for optimal performance.
- Train, tune, and deploy anomaly detection and predictive models on industrial or IoT data.
- Knack/experience in 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), and Kubeflow – desirable.
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.
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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
Familiarize yourself with the specific ML/AI libraries mentioned in the job description, such as NumPy, pandas, and scikit-learn. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your readiness to contribute to our data science team.
✨Tip Number 2
Showcase any previous projects where you have successfully delivered machine learning models to production. Be prepared to discuss the challenges you faced and how you overcame them, as this will highlight your problem-solving skills and practical experience.
✨Tip Number 3
Brush up on your knowledge of SQL and data pipelines, as interfacing with various data sources is a key responsibility. Being able to discuss your experience with SQL and how you've used it in past projects will set you apart from other candidates.
✨Tip Number 4
Demonstrate your ability to work collaboratively by sharing examples of successful teamwork in your previous roles. Highlighting your stakeholder management skills and how you've influenced project outcomes will resonate well 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 relevant experience in data science, particularly any hands-on work with machine learning models. Emphasize your proficiency in Python and the specific libraries mentioned in the job description.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific projects or experiences that align with the responsibilities listed, such as working with AI/ML algorithms or developing predictive models.
Showcase Your Technical Skills: Include a section in your application that showcases your technical skills, especially those related to SQL, Power BI, and any experience with Azure or Spark. This will help demonstrate your fit for the position.
Highlight Team Collaboration: Since the role involves working closely with a team, provide examples of past collaborative projects. Highlight your ability to communicate effectively with colleagues and stakeholders, as this is crucial for success in the position.
How to prepare for a job interview at Sneak Peek Tech
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with data science libraries like NumPy, pandas, and scikit-learn. Highlight specific projects where you successfully delivered machine learning models to production.
✨Demonstrate Your Problem-Solving Abilities
Prepare examples of how you've tackled complex data challenges in the past. Discuss your approach to building algorithms for anomaly detection and predictive modeling, and be ready to explain your thought process.
✨Emphasize Team Collaboration
Since you'll be working closely with senior team members, share experiences that showcase your ability to collaborate effectively. Talk about how you’ve contributed to team projects and supported colleagues in achieving common goals.
✨Express Your Willingness to Learn
Convey your enthusiasm for learning new technologies and techniques. Mention any relevant courses or certifications you've pursued, and express your interest in exploring tools like Azure, Spark, and Kubeflow.
