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- Tasks: Transform complex data into insights and develop predictive models.
- Company: Lumora Solutions, a leader in data-driven innovation.
- Benefits: Work with cutting-edge tech in a collaborative, learning-focused environment.
- Why this job: Make a real impact by solving complex data challenges.
- Qualifications: Experience in data modelling, analytics, and programming skills required.
- Other info: Great opportunities for professional growth and continuous learning.
The predicted salary is between 28800 - 48000 £ per year.
This range is provided by Lumora Solutions. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Location: Manchester (Hybrid)
Summary: The ideal candidate's favourite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.
Objectives:
- Transform complex data into meaningful insights that drive smarter business decisions.
- Develop and deploy scalable predictive models and algorithms to support growth.
- Collaborate across teams to translate analytical findings into actionable strategies.
- Continuously learn and apply new techniques to enhance agility and impact at scale.
Responsibilities:
- Analyse raw data: assessing quality, cleansing, structuring for downstream processing.
- Design accurate and scalable prediction algorithms.
- Collaborate with engineering team to bring analytical prototypes to production.
- Generate actionable insights for business improvements.
Skills & Experience:
- Proven experience in data modeling, predictive analytics, and machine learning techniques.
- Proficiency in programming (Python, SQL, Java, or C/C++) with exposure to Big Data and visualization tools.
- Strong analytical and problem-solving skills with the ability to extract actionable insights from complex datasets.
- Excellent collaboration and communication skills, with a passion for continuous learning and working at scale.
What’s in it for you:
- Opportunity to work with cutting-edge technologies and solve complex, real-world data challenges.
- A collaborative, learning-driven environment that values innovation, agility, and professional growth.
Seniority level: Mid-Senior level
Employment type: Contract
Job function: Engineering and Information Technology
Industries: IT Services and IT Consulting, Retail, Financial Services
Data Scientist in Manchester employer: Lumora Solutions
Contact Detail:
Lumora Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with data science communities. 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 predictive models and data visualisation. 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 practising common data science questions. Don’t forget to highlight your collaboration skills and how you’ve turned complex data into actionable insights in past roles.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search and eager to join our learning-driven environment.
We think you need these skills to ace Data Scientist in Manchester
Some tips for your application 🫡
Show Your Passion for Data: When you're writing your application, let your love for data shine through! Talk about your experiences with data modelling and predictive analytics, and how they’ve shaped your journey. We want to see that you’re not just skilled, but genuinely excited about the work you do.
Tailor Your Application: Make sure to customise your application for the Data Scientist role. Highlight relevant skills like programming in Python or SQL, and any experience with Big Data tools. This shows us that you understand what we’re looking for and that you’re a great fit for our team.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your achievements and skills. We appreciate when candidates can communicate complex ideas simply, as this reflects the collaboration we value at StudySmarter.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Lumora Solutions
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects involving data modelling and predictive analytics. Be ready to discuss specific challenges you faced, how you approached them, and the outcomes. This shows your hands-on experience and problem-solving skills.
✨Brush Up on Your Programming Skills
Make sure you're comfortable with the programming languages mentioned in the job description, especially Python and SQL. Prepare to answer technical questions or even solve coding problems during the interview. Practising common algorithms and data structures can give you an edge.
✨Showcase Your Collaboration Skills
Since collaboration is key for this role, think of examples where you've worked with cross-functional teams. Highlight how you translated complex data insights into actionable strategies that benefited the business. This demonstrates your ability to communicate effectively and work well with others.
✨Stay Curious and Open to Learning
Emphasise your passion for continuous learning and adapting to new techniques. Share any recent courses or certifications you've completed related to data science. This aligns perfectly with the company's values and shows you're committed to growing in your field.