At a Glance
- Tasks: Lead data science initiatives, build intelligent models, and analyse data for impactful business solutions.
- Company: Join Nomo Fintech, a dynamic cloud-based B2B fintech company revolutionising digital banking.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth in a fast-paced environment.
- Other info: Collaborative team culture with mentorship opportunities and career advancement.
- Why this job: Be at the forefront of data science, driving innovation in the fintech industry.
- Qualifications: STEM degree, 2-3 years in data analytics, and experience with machine learning techniques.
The predicted salary is between 70000 - 90000 £ per year.
Who we are
BB2 Digital and Technology Services Ltd (t/a Nomo Fintech) is a cloud-based business-to-business Fintech company which owns the digital platform that powers the digital retail banking services of Bank of London and The Middle East plc (“BLME”), branded Nomo (available on iOS and Android), and provides various other services to BLME. Nomo Fintech is currently in scale-up mode to support international digital banking across the GCC, and it’s an incredibly exciting time to join the business with great ambition and an effective combination of talent, culture, and world class technology. Nomo Fintech leverages the support services of an intragroup entity based in Dubai which houses various functions to support Nomo Fintech’s business services.
DESCRIPTION
The role of the lead data scientist is focused on building and running the data science discipline and delivery mechanisms for data science artefacts internally. The Lead data scientist is a person who generates value by “putting our data to work” through the use of intelligent systems. Working with data engineers and data analytics teams to make advanced calculations to derive conclusions. As a lead data scientist you will receive data that has passed a first round of cleaning and modelling, which you then can feed to sophisticated analytics models, machine learning and statistical methods to automate decisions. The lead data scientist will have high levels of autonomy and responsibility for intelligent systems and related artefacts and would suit a candidate that wants to join an existing data science team and help us level up.
RESPONSIBILITIES
- The lead data scientist will have to do the following key functions (Data exploration and visualization, experimentation and prediction):
- Capture the sources of data and analyses them to build the best Intelligent models.
- Key Models to be built as a team: LTV, Churn, Portfolio Risk, Creditworthiness/affordability, Behavior Economics.
- Design intelligent systems and work with Data Engineers to utilise technologies to convert unstructured data into structured data and embeddings.
- Reviewing Payments and Purchasing Habits across all customer segments.
- Present and explain data to others. They must be able to communicate data to people of different skill sets, explain the importance of patterns in the data, and suggest solutions.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from company databases to drive optimization and improvement of our products, marketing techniques and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
- Develop company A/B testing framework and test model quality.
- Create visualisations to communicate insights to management and stakeholders across the company.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Manage and mentor other data scientists.
TYPICAL SKILLS & BACKGROUND
- Key background: Statistics, Econometrics, Computer Science (Will have a STEM degree discipline).
- Proficiency in statistical software packages and functional programming languages (any of the following SQL, SPSS, R, Python, Wolfram Mathematica and C++, or Java).
- Will have at least 2-3 years of financial services-based, data analytics experience. Preferably experience within the fraud and financial crime domain, or card payments.
- Will have experience working with multiple and large unstructured datasets.
- Experience in an analytical role involving machine learning techniques, data extraction, analysis, and communication.
- Experience designing and implementing machine learning algorithms tailored to specific business needs and tested on large datasets.
- Experience in data mining and using databases in a business environment with large-scale, complex datasets.
- Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences.
- Experience running teams of around 5 including a range of abilities from associate/intern level through to principal level.
Lead Data Scientist employer: Nomo Fintech
Nomo Fintech is an exceptional employer, offering a dynamic work environment in the heart of Dubai's thriving fintech scene. With a strong focus on employee growth and development, we provide opportunities for our team members to advance their skills in data science while working with cutting-edge technology. Our collaborative culture encourages innovation and creativity, making it an exciting time to join as we scale up our international digital banking services across the GCC.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those that highlight your experience with machine learning and predictive modelling. This will give you an edge when chatting with hiring managers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and being ready to discuss your past experiences. Practice explaining complex data concepts in simple terms, as you'll need to communicate effectively with various stakeholders.
✨Tip Number 4
Don't forget to apply 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 awesome team at Nomo Fintech.
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with data analytics, machine learning, and any relevant projects that showcase your skills. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with our mission at Nomo Fintech. Let us know what excites you about this opportunity!
Showcase Your Technical Skills:Don’t forget to mention your proficiency in statistical software and programming languages like SQL, Python, or R. We’re looking for someone who can hit the ground running, so make sure we see your technical chops!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. We can’t wait to hear from you!
How to prepare for a job interview at Nomo Fintech
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning algorithms and statistical methods. Be ready to discuss specific projects where you've applied these techniques, as well as the outcomes. This will show that you can not only understand complex data but also translate it into actionable insights.
✨Showcase Your Communication Skills
As a lead data scientist, you'll need to explain complex data concepts to non-technical stakeholders. Prepare examples of how you've successfully communicated data findings in the past. Think about how you can simplify technical jargon and make your insights relatable to different audiences.
✨Demonstrate Team Leadership
Since this role involves managing a team, be ready to share your experiences in mentoring and leading data scientists. Highlight any strategies you've used to foster collaboration and innovation within your team. This will help them see you as a strong candidate who can elevate their existing data science team.
✨Prepare for Technical Questions
Expect some technical questions or case studies during the interview. Practice solving problems on the spot, especially those related to data exploration, model building, and performance monitoring. This will demonstrate your analytical thinking and problem-solving skills, which are crucial for the role.
