Data Scientist Intern
Type: Intern to possible full-time hire
Who is FNA?
FNA is a fast growing, deep technology company rooted in finance. Our flagship product, the FNA Platform allows financial institutions to map and monitor complex financial networks and to simulate operational and financial risks. Over a decade of pioneering research into financial graph analytics makes the company a leader in its field. FNA’s clients include the world’s largest central banks, financial market infrastructures and financial institutions. FNA’s mission is to bring graph analytics to the financial services mainstream and to play a pivotal role in the growing graph analytics ecosystem, where FNA’s engine powers use cases across a growing number of business domains.
What are the benefits of joining FNA?
- FNA’s mission is to make our global financial systems safer and more efficient
- Opportunity to expand your career with additional duties and job titles as the company grows
- High-growth start-up working on the development of exciting next generation, machine learning, and Big-Data analytics solutions
- Be part of a team of collaborative, brilliant, passionate, hard-working & humble colleagues who embrace working from anywhere there is a solid internet connection
- Entrepreneurial spirit at every level of the company
- FNA fully supports and encourages and assists in your personal and professional growth
Key areas of responsibility
- You will be actively involved in the research and development of exciting new use-cases
- Using the FNA platform and scripting language, you will be assisting to identify hidden behavioural patterns and interconnections in large datasets, helping to create breakthrough solutions, performing exploratory and targeted data analyses as part of quantitative services engagements or proof of concepts
- Partner with cross-functional teams to solve business problems at scale and identify trends/opportunities for the customers
- You will document use cases in technical reports, white papers, etc.
- You should be enrolled as a Ph.D. student in Finance/Econometrics, Data Science, Machine Learning, Statistics, Mathematics, or related applied quantitative field
- Passion and curiosity for what is happening within RegTech/FinTech/SupTech, Big Data, Graph Databases, Data Analysis or especially Graph Analytics
- Experience with MatLab, Python, R or similar
- Experienced with, or have a desire to learn Network Science and/or Graph Analytics
- Hands-on and curious; always looking to learn and improve your technical skills
- Strong written documentation skills to assist with articles/use-cases/releases etc.
- Excellent written and spoken English