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- Tasks: Build predictive models and run simulations using complex datasets.
- Company: Join a collaborative team focused on innovative research.
- Benefits: Competitive salary, flexible work environment, and opportunities for growth.
- Why this job: Make an impact by turning research into production-ready code.
- Qualifications: Strong background in statistics, Python skills, and familiarity with ML/AI methods.
- Other info: Dynamic role with a focus on improving research tools and practices.
The predicted salary is between 60000 - 80000 £ per year.
Our client is seeking a seasoned Systematic Futures Researcher with expertise in alternative data to join their collaborative team.
Responsibilities of the Role:
- Build predictive models with large, complex datasets.
- Run simulations to test hypotheses on a high-performance compute grid.
- Turn research into clean, production-ready code.
- Add safeguards: sanity checks, drift detection, anomaly monitoring.
- Improve their research platform and tooling so everyone can move faster.
Requirements of the Role:
- Strong foundation in probability, statistics, and linear algebra.
- Solid intuition for ML/AI methods.
- Strong Python skills; ability to read C++.
- Knowledge of algorithms, data structures, and performance optimization.
- Comfortable with Linux/Unix, Git, and modern dev practices (tests, CI/CD, containers).
- Clear communicators who take initiative.
Systematic Futures Researcher - Predictive Modeling employer: Qenexus
Contact Detail:
Qenexus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Systematic Futures Researcher - Predictive Modeling
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and simulations. We love seeing real examples of your work, so make sure to highlight your Python prowess and any cool projects you've tackled.
✨Tip Number 3
Prepare for those interviews! Brush up on your probability, statistics, and ML/AI methods. We recommend running through some common interview questions and even doing mock interviews with friends to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for clear communicators who take initiative, just like you!
We think you need these skills to ace Systematic Futures Researcher - Predictive Modeling
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your strong foundation in probability, statistics, and linear algebra. We want to see how your expertise aligns with the role, so don’t hold back on showcasing your Python skills and any experience you have with C++.
Be Clear and Concise: When writing your application, clarity is key! We appreciate clear communicators, so make sure your thoughts are well-organised and easy to follow. This will help us understand your thought process and how you approach problem-solving.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your application to the specific role of Systematic Futures Researcher. Mention your experience with predictive modelling and alternative data, and how you can contribute to improving our research platform.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important details. Plus, it shows you’re keen to join our collaborative team!
How to prepare for a job interview at Qenexus
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of alternative data relevant to the role. Brush up on your knowledge of predictive modelling and be ready to discuss how you've used large datasets in past projects.
✨Show Off Your Coding Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice writing clean, production-ready code and be familiar with C++ basics.
✨Understand the Algorithms
Be prepared to talk about algorithms, data structures, and performance optimisation. Think of examples from your experience where you’ve applied these concepts effectively, and be ready to explain your thought process.
✨Communicate Clearly and Confidently
As clear communication is key, practice explaining complex concepts in simple terms. Be proactive in the conversation, ask insightful questions, and show that you can take initiative in discussions.