At a Glance
- Tasks: Develop and deploy machine learning models to transform data into actionable insights.
- Company: Join a leading fintech firm revolutionising global payments with innovative technology.
- Benefits: Competitive salary, bonus opportunities, and rapid career progression in a dynamic environment.
- Other info: Mentorship opportunities and a culture that values entrepreneurship and innovation.
- Why this job: Make a real impact by working on cutting-edge data science projects in a collaborative team.
- Qualifications: Experience in Python, machine learning, and big data technologies like Spark and Hadoop.
The predicted salary is between 63000 - 77000 £ per year.
Python Data Scientist – Fintech80,000 Plus Bonus Quant Capital is urgently looking for a Senior Data Scientist to join or well known Fintech50 client.
Our client is a well-known cloud based fintech in the global payments and e invoicing space.
They are a tech firm driven buy large scale data with huge enterprise clients.
You will be joining a team that has built up an internal data warehouse serving multiple lines of businesses in the organization.
A rapidly growing code-base, trained upon the data warehouse, is delivering descriptive and predictive business insights.
The next step of this journey is to bring the machine learned models directly into production environments as part of the Data Science and Machine Learning as a Platform initiative.
Your chief responsibilities will be to develop further client facing machine learning use cases across multiple lines of businesses and to oversee the end-to-end pipeline of transforming the selected use-cases into performance code and deploying them into production.
In addition to Python you should also be familiar with at least one compiled language such as Java or C#.
They are growing massively with clients and internal infrastructure moving to the cloud as well as Infrastructure as code.
The Data Scientist should have:·Demonstrable hands-on experience in deploying and maintaining machine learning models in production environments·Processing massive amounts of structured and unstructured data using Spark/SQL/Hive·Familiar with offline (batch) and online (live/stream) data pipelines·Writing production code in Python·Understanding the full software development life-cycle (conduct data analysis and build large-scale machine-learning models/pipelines)·Exposure to the state-of-the-art data analytics products and solutions·Carrying out A/B test experiments·Experience in Big Data technologies (Hadoop, Spark)·Experience in data pre-processing, Machine Learning, and data visualisation·Experience with large relational and No SQL databases·Communicating findings to non-technical audience·Mentoring and supporting junior data scientists and analysts·Comfortable running SQL queries to fetch data from the internal data-store The firm has a corporate feel but relies on entrepreneurship within its staff.
It rewards on a pure merit basis with rapid progression actively encouraged.
This team has a strong reputation in the market as breeding quick thinkers and adding real value to SME’s My client is based near Reading Scala, Data Science, Python, Numpy, Machine Learning, Hadoop
Senior Data Scientist- Reading in London employer: Quant Capital
Quant Capital is an excellent employer for those looking to thrive in the fintech sector, offering a vibrant work culture that fosters innovation and collaboration. With substantial training and development opportunities, employees can enhance their skills while enjoying a flexible hybrid work model in the heart of London. Join us to be part of a forward-thinking team that values growth and cutting-edge technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist- Reading in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Quant Capital.
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We think you need these skills to ace Senior Data Scientist- Reading in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Quant Capital, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Quant Capital. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Quant Capital
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Quant Capital!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
