Data Scientist - Asia

Department: Client Success

Location: This is a fully remote role although Jakarta Indonesia is preferred

Term: Full time | Permanent 

Mission: Founded in 2014, FNA’s mission is to make the financial system safer and more efficient. 

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Why this role is important

About the role

As a Data Scientist at FNA, you will accelerate the development of our award-winning analytics software, while implementing and delivering important data science solutions for some of the world's largest and most influential institutions.

Apply your curiosity of machine learning and network science whilst working with a selective team of brilliant data scientists who challenge the status quo daily and are quietly pushing forward the bleeding edge of network analytics with our advanced platform.   

• Implement FNA’s solutions to the world’s largest central banks, financial market infrastructures and commercial banks.
• Actively participate as a contributing member on a team of data scientists through the whole workflow, from data access, processing and modeling, to data visualization 
• Partner with internal FNA stakeholders and client subject matter experts to refine analyses, gain insights and present new findings
• Develop and present client-specific solutions clearly and concisely, communicate analyses, recommendations, status and results to existing clients and prospects at business management and executive level
• Operationalize models into production with the FNA Platform
• Carry out research and development of new use-cases, algorithms and solutions - either as part of our product road-map or based on specific client requirements
• Act as product owner for specific features or models implemented in the FNA Platform
• Resolve client support requests in a professional and timely manner.

Why join FNA? 

• Own and deliver meaningful work with a global impact
• Rapidly advance your career, thinking and skills in a high growth tech company
• Collaborate with a diverse, international team of innovative and high-achieving colleagues
• Annual budget for personal and professional development
• Flexible, remote working since 2014
• International team off-sites 
• We reward curiosity, initiative, execution and reliability with opportunity
• Company share options 

Who we’re looking for 

• The right candidates will have at minimum 2+ years experience as a Data Scientist in commercial or academic projects applying Network Science & Machine Learning models and presenting your results to stakeholders
• You should be a team player who picks up implicit tasks, is self-organized and self-motivated, embraces autonomy and working remotely but enjoys the occasional travel to interface with clients for implementations, training and use case exploration
• The right candidate is naturally inquisitive with the ability to communicate technical findings to non-technical personnel and isn’t afraid to present creative, data-driven ideas to stakeholders
• Proficiency in data query and programing languages (Python/R/MATLAB/SQL/Java)
• Passion and curiosity for what is happening within RegTech/FinTech/SupTech, Cybersecurity and Cyber Threat Intelligence, Graph Databases and especially Graph Theory/Network Science
• Efficiently balances accuracy and speed while getting things done 
• You're a team player with tenacity underpinned by self-awareness and empathy
• Fluent written and spoken English. Additional languages are a benefit. 
• Ability to travel approximately <25% of the time (Domestic and International)

Nice To Haves:

• MSc or PhD level qualification in mathematics, statistics, computer science, economics, finance, physics, engineering or related applied quantitative field  

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About FNA

FNA is a leader in advanced network analytics and simulation.

Our software is used to uncover hidden connections and anomalies in large, complex datasets, to predict the impact of stress events, and to optimally configure financial systems and infrastructures.

FNA is trusted by the world’s largest central banks, government authorities, commercial banks and financial infrastructures.