At a Glance
- Tasks: Prototype and deploy complex analytics models while collaborating with a passionate team.
- Company: Join Envelop Risk, a cutting-edge underwriting agency in cyber insurance.
- Benefits: Flexible work environment, international travel opportunities, and professional development.
- Other info: Dynamic team culture with excellent career growth potential.
- Why this job: Make an impact in the world of cyber risk with innovative technology.
- Qualifications: Proficiency in Python and experience in data analytics pipeline required.
The predicted salary is between 36000 - 60000 £ per year.
Envelop Risk is a rapidly-growing underwriting agency combining world leaders in (re)insurance underwriting and artificial intelligence-based simulation modelling. The firm underwrites cyber reinsurance contracts and is building cyber insurance products that will be distributed globally. Envelop is seeking technical staff for a new office in Bristol, that will serve as the new global hub for its modelling and technology team.
Envelop Risk offers a flexible, equal-opportunity workplace with an engaged and talented team delivering high-quality projects on the cutting edge of technology. Occasional international travel for client workshops and technical networking will be required.
Envelop’s Mission
To create the world’s leading cyber risk underwriting agency, we combine state of the art analytics with unrivalled underwriting and client insight. We select and transfer risk in the most informed and efficient manner possible and utilize a range of innovative distribution and capacity channels to facilitate the optimum value chain for cyber risk transfer.
Job Description
Envelop is seeking a talented data scientist with a background in machine learning and in taking data science solutions through to production. The role will require interaction with clients and collaboration with Envelop’s passionate team of data scientists, software engineers and underwriters, shaping data analytics solutions to meet client needs. Insurance and cyber security experience are not required, but either would be looked upon favourably.
Responsibilities
- Prototype, develop, and deploy complex analytics models
- Acquire, process, and model large, complex datasets
- Work in an internationally distributed team, with schedule flexibility
- Deliver high quality technical outcomes while adhering to cost and schedule constraints
- Continue technical and professional development to ensure Envelop’s technology and its team remains on the cutting edge
Required skills
- Proficiency in Python and common data science packages such as SciKit-Learn, NumPy and Pandas
- Experience in all portions of the data analytics pipeline, including ingest, cleaning, feature extraction, modelling, statistical validation, and visualization / reporting
- Competence in software development practices including writing and verifying maintainable code, version control, cloud-based development, and performance profiling and tuning
Desired skills
- Expertise in one or more of: probabilistic modeling, natural language processing, explainable AI, uncertainty analysis, time series analysis
- Strong data visualization and data 'storytelling' skills
- Analytics experience in finance, insurance, or cyber security
- Proficiency in other analytics technologies, such as R, SQL, CUDA, Hadoop, Spark, and Redshift
- Experience with Dataiku's Data Science Studio
Qualifications
- Bachelor of Science or higher in engineering, science, or mathematics, with specializations related to computer science preferred
- Minimum of 3 years relevant experience, including internships, part-time positions, and graduate level education
Additional Information
This role is committed to ensuring that all of its employees are legally eligible to be employed in the United States and refrains from discriminating against individuals on the basis of national origin or citizenship. Within three (3) days of being hired, the candidate must submit a Form I-9 and utilizes E-Verify to confirm employment eligibility.
Data Scientist, Envelop UK in Bristol employer: QxBranch
Envelop Risk is an exceptional employer, offering a dynamic and flexible work environment in Bristol, where innovation meets collaboration. With a focus on cutting-edge technology and a commitment to employee growth, team members are encouraged to develop their skills while working on impactful projects in the rapidly evolving field of cyber risk. The inclusive culture and opportunities for international networking make Envelop an attractive choice for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist, Envelop UK in Bristol
✨Tip Number 1
Network like a pro! Reach out to current employees at Envelop Risk on LinkedIn. A friendly message can go a long way in getting your foot in the door and showing your genuine interest in the company.
✨Tip Number 2
Prepare for those interviews! Brush up on your Python skills and be ready to discuss your experience with data analytics. We recommend practising common data science interview questions to boost your confidence.
✨Tip Number 3
Showcase your projects! If you've worked on any relevant data science projects, make sure to highlight them during your conversations. We love seeing how you’ve applied your skills in real-world scenarios.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows that you’re proactive and really want to be part of the Envelop team.
We think you need these skills to ace Data Scientist, Envelop UK in Bristol
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role at Envelop. Highlight your experience with Python and data science packages, and don’t forget to showcase any relevant projects that demonstrate your skills in machine learning and analytics.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about working at Envelop and how your background aligns with their mission. Be sure to mention any experience you have with data analytics and how you can contribute to their team.
Showcase Your Projects:If you’ve worked on any interesting data science projects, make sure to include them in your application. Whether it’s a personal project or something from a previous job, showing off your work can really set you apart from other candidates.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Envelop!
How to prepare for a job interview at QxBranch
✨Know Your Data Science Stuff
Make sure you brush up on your Python skills and the data science packages mentioned in the job description, like SciKit-Learn, NumPy, and Pandas. Be ready to discuss your experience with the entire data analytics pipeline, as this will show that you can hit the ground running.
✨Show Off Your Problem-Solving Skills
Prepare to talk about specific projects where you've prototyped, developed, or deployed analytics models. Use examples that highlight your ability to tackle complex datasets and deliver high-quality outcomes under tight deadlines. This will demonstrate your practical experience and problem-solving capabilities.
✨Get Familiar with Cyber Risk
Even though insurance and cyber security experience aren't required, having a basic understanding of these areas can give you an edge. Do some research on cyber risk underwriting and think about how your data science skills can apply to this field. It shows you're proactive and genuinely interested in the role.
✨Be Ready for Team Collaboration
Since you'll be working with an internationally distributed team, be prepared to discuss your experience in collaborative environments. Highlight any past experiences where you've worked with diverse teams or clients, and how you adapted to different schedules and communication styles. This will show that you're a team player who can thrive in a flexible workplace.
