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For Companies At a Glance
- Tasks: Transform data into insights and build predictive models using cutting-edge technology.
- Company: Join a forward-thinking tech company that values innovation and creativity.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team tackling real-world challenges with data science and machine learning.
- Qualifications: 5-10 years in software engineering with expertise in Python, R, and machine learning.
- Other info: Knowledge of AKS and C# is a plus; strong communication skills are essential.
The predicted salary is between 48000 - 72000 £ per year.
Job Brief:
Brief Summary of Responsibilities:
- Undertake preprocessing of structured and unstructured data
- Present information using data visualization techniques
- Propose solutions and strategies to business challenges
- Identify valuable data sources and automate collection processes
- Analyze large amounts of information to discover trends and patterns
- Build predictive models, machine-learning algorithms and publish them in Cloud.
- Writing reusable, testable, and efficient code
- Support the front-end developers by integrating their work with the Python application.
Qualifications / Skills:
- B.E. in Computer Science/Information Science
- 5-10 years of experience
- Experience using statistical computer languages (Python, R) to manipulate data and draw insights from large data sets.
- Experience in Machine Learning, NLP, ML framework, and deploying ML models in Cloud . Knowledge of AKS is an advantage.
- Must have knowledge of SQL and MS Excel.
- Knowledge of C# is desirable.
- Communicate proficiently internally and externally, with technical and non-technical audiences
Skills Required:
MLflow, NLP, Predictive Modelling, ML Framework, Accuracy, Transfer Learning
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Contact Detail:
Recooty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Software Engineer-Data Science
✨Tip Number 1
Familiarise yourself with the latest trends in data science and machine learning. Being able to discuss recent advancements or tools during your interview can demonstrate your passion and commitment to the field.
✨Tip Number 2
Prepare to showcase your experience with Python and R by discussing specific projects where you manipulated data or built predictive models. Real-world examples can help illustrate your skills effectively.
✨Tip Number 3
Brush up on your SQL and Excel skills, as these are crucial for the role. You might be asked to solve problems or analyse data on the spot, so being confident in these areas will give you an edge.
✨Tip Number 4
Practice explaining complex technical concepts in simple terms. Since you'll be communicating with both technical and non-technical audiences, being able to convey your ideas clearly is essential.
We think you need these skills to ace Senior Software Engineer-Data Science
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, R, and machine learning. Include specific projects where you've used these skills, especially in data preprocessing and predictive modelling.
Craft a Strong Cover Letter: In your cover letter, explain how your background aligns with the responsibilities listed in the job description. Mention your experience with cloud deployment and any relevant projects that demonstrate your ability to solve business challenges using data.
Showcase Your Technical Skills: Be explicit about your proficiency in SQL, MS Excel, and any experience with AKS or C#. Provide examples of how you've integrated front-end work with Python applications in past roles.
Prepare for Technical Questions: Anticipate technical questions related to machine learning algorithms and data visualisation techniques. Be ready to discuss your approach to building predictive models and any challenges you've faced in previous projects.
How to prepare for a job interview at Recooty
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, R, and any machine learning frameworks you've used. Highlight specific projects where you've applied these skills, especially in data manipulation and predictive modelling.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your ability to propose solutions to business challenges. Think of examples where you've identified valuable data sources or automated collection processes, and be ready to explain your thought process.
✨Communicate Clearly
Since the role requires communicating with both technical and non-technical audiences, practice explaining complex concepts in simple terms. This will show your ability to bridge the gap between different stakeholders.
✨Prepare for Practical Assessments
You might be asked to complete a coding challenge or a case study during the interview. Brush up on writing reusable and efficient code, and be ready to demonstrate your skills in integrating front-end work with Python applications.
