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- Tasks: Join our data team to develop machine learning algorithms and build data pipelines.
- Company: Dynamic tech company in London focused on data-driven solutions.
- Benefits: Professional growth, flexible work options, and a collaborative environment.
- Why this job: Make an impact by solving real-world challenges with cutting-edge technology.
- Qualifications: Master's degree in relevant field and foundational knowledge of machine learning.
- Other info: Inclusive culture that values diversity and fosters career development.
The predicted salary is between 28800 - 43200 £ per year.
We are looking for a motivated Junior Machine Learning Engineer to join our data team and contribute to the development of data-driven solutions. This entry-level position offers an excellent opportunity to build your analytical skills, work with real-world datasets, and gain hands-on experience with machine learning and statistical techniques. You’ll work closely with senior data scientists and engineers to support various projects and deliver insights that drive decision-making. If you’re curious, eager to learn, and passionate about using data to solve complex problems, we’d love to hear from you.
Responsibilities
- Strong understanding of Object-Oriented Programming (OOP) principles.
- Designing machine learning algorithms.
- Develop and test machine learning algorithms to address business needs, ensuring high accuracy and scalability.
- Building data pipelines. Design and manage data pipelines that handle large datasets, data preprocessing, feature engineering, and efficient data flow to ensure high-quality input for machine learning models.
- Optimizing models. Use tools like scikit-learn and Keras to fine-tune models for enhanced model performances.
- Perform exploratory data analysis to identify patterns and insights.
- Develop and test statistical models and machine learning algorithms under guidance.
- Create user-friendly visualizations to communicate findings.
- Support the development of dashboards and reporting tools for stakeholders.
- Collaborate with team members across departments to understand data needs and project goals.
- Stay updated with new trends and best practices in data science and analytics.
- Document methodologies, data workflows, and project findings for reference and reproducibility.
Required Skills & Education
- Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
- Foundational understanding of data analysis, statistics, and machine learning.
- Proficiency in programming languages such as Python or R.
- Basic knowledge of SQL and working with relational databases.
- Familiarity with data visualization tools like Tableau, Power BI, or Matplotlib.
- Strong problem-solving and critical-thinking skills.
- Eagerness to learn and grow in a fast-paced, collaborative environment.
- Excellent communication skills and a team-focused mindset.
Nice-to-Have Skills
- Exposure to cloud platforms like AWS, Azure, or GCP.
- Experience with data manipulation libraries like pandas or NumPy.
- Familiarity with APIs and working with large datasets.
- Understanding of version control systems like Git.
Why Join Us?
- Professional Growth: Gain invaluable experience and mentorship to develop your career.
- Impactful Work: Take part in projects that solve real-world challenges.
- Collaborative Team: Work in an environment that values collaboration and shared learning.
- Flexibility: Enjoy opportunities for remote or hybrid work to support work-life balance.
- Inclusive Culture: Be part of a diverse workplace that values each individual’s contribution and fosters equity and belonging.
Junior Machine Learning Engineer employer: Information Tech Consultants
Contact Detail:
Information Tech Consultants Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Machine Learning Engineer
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even local tech events. You never know who might be looking for a Junior Machine Learning Engineer or who can refer you to someone who is.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving machine learning algorithms or data visualisations. Share it on platforms like GitHub or your personal website, and don’t forget to link it in your applications!
✨Ace the Interview
Prepare for technical interviews by practising coding challenges and understanding key concepts in machine learning. Be ready to discuss your past projects and how you approached problem-solving. Confidence is key!
✨Apply Through Our Website
Don’t forget to check out our careers page and apply directly through our website. It shows initiative and gives you a better chance of getting noticed by our hiring team!
We think you need these skills to ace Junior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that match the Junior Machine Learning Engineer role. Use keywords from the job description to show we’re on the same page!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data and machine learning, and explain why you want to join our team at StudySmarter. Keep it personal and engaging.
Showcase Your Projects: If you've worked on any projects related to machine learning or data analysis, don’t hold back! Include links to your GitHub or any relevant portfolios to give us a taste of your skills.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Information Tech Consultants
✨Know Your Algorithms
Brush up on your understanding of machine learning algorithms. Be ready to discuss how you would design and optimise them for specific business needs. Having examples from your past projects can really help demonstrate your knowledge.
✨Showcase Your Coding Skills
Since proficiency in Python or R is crucial, be prepared to solve coding challenges during the interview. Practise common data manipulation tasks using libraries like pandas or NumPy, as this will show your hands-on experience.
✨Prepare for Data Visualisation Questions
Familiarise yourself with data visualisation tools like Tableau or Matplotlib. Be ready to explain how you would create user-friendly visualisations to communicate findings effectively. This shows you can translate complex data into understandable insights.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s projects, the company culture, and opportunities for professional growth. This not only shows your interest but also helps you gauge if the role is the right fit for you.
