Data Science Manager

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Client: A single family office of international and long-standing repute. Joining their digital tech VC fund. A very exciting opportunity for an experienced data science manager with strong programming and machine learning skills. A key and integral position within the company offering a super challenge and a rewarding job for a scientist! This is a client that Finders know well and are the exclusive head-hunter on this mandate.

Client: A single family office of international and long-standing repute. Joining their digital tech VC fund. A very exciting opportunity for an experienced data science manager with strong programming and machine learning skills. A key and integral position within the company offering a super challenge and a rewarding job for a scientist! This is a client that Finders know well and are the exclusive head-hunter on this mandate.

Data Science Manager

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Position: Are you an experienced data scientist keen to join a boutique fund going from strength to strength and passionate about financial services? This could be just the challenge you’ve been waiting for! Used to crunching a lot data, you are perhaps a data scientist at a hedge fund or asset manager today or within financial services or a large corporate and looking to get your teeth into something new? This is a broad role where you can be visible within the small but growing company. Reporting to the Managing Director, and working closely with the Investment Team, this newly-created role is supporting a growing digital VC fund company in the tech space of a leading family office group of companies. Essentially you should have a very broad data science experience from an operational point of view as well as coding - as you be key in the enhancement and development of their existing platform and take it to the next stage. This position is for a pragmatic person who can apply knowledge on very specific, practical cases - to show results - so you should therefore be able to implement and "fix things". Your combined experience will encompass not only being able to code but also to set up a data base, able to develop in HTML for example, build some interfaces on all those aspects, to also of course include pathways and algorithms. Your key responsibilities and tasks will include but not limited to: Scope Design experiments, test hypotheses, and build models Apply advanced statistical and predictive modelling techniques to build, maintain, and improve on multiple realtime decision systems Conduct advanced data analysis and highly complex designs algorithm Business Requirements Lead discovery processes with the investment team to identify the business requirements and the expected outcome Work with and alongside analysts by suggesting other features of interest Model and frame business scenarios that are meaningful and which impact on critical business processes and/or decisions Data Requirements Identify what data is available and relevant, including internal and external data sources, leveraging new data collection processes Make strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices Collaborates with the fund’s subject matter experts to select the relevant sources of information Analysis Develop innovative and effective approaches to solve the fund company’s analytics problems and communicate results and methodologies Work in iterative processes with the team and validates findings Develop experimental design approaches to validate finding or test hypotheses Validate analysis using scenario modelling Identify/create the appropriate algorithm to discover patterns Qualification and Assurance Assess, with the investment team, opportunities to enhance the qualification and assurance of the information to strengthen the use case Define the validity of the information, how long the information is meaningful, and what other information it is related to Access Management and Control Work with the compliance and IT teams to ensure that the information used is in compliance with the regulatory and security policies in place Qualify where information can be stored or what information, external to the organization, may be used in support of the use cases Utilize patterns and variations in the volume, speed and other characteristics of data supporting the needs, the type of data (e.g., images, text, …) in predictive analysis Policies, Standards and Procedures Develop usage and access control policies and systems in collaboration with the data owners Partner with the data owners in continuous improvement processes impacting data quality in the context of the specific use cases Recommend ongoing improvements to methods and algorithms that lead to findings, including new information Communications/ Presentations Present and depicts the rationale of the findings in easy to understand terms for the team Present back results that contradict common belief, if needed Communicate and work with the analysts, subject matter experts and organizational leadership Change Advocacy Educate the team both from IT and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results Help the team understand the principles and the maths behind the process to drive organizational buy-in Metrics Provide business metrics to show improvements (contribution to the improvement should be monitored initially and over multiple iterations) Demonstrate the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, and fairness Performance Provide on-going tracking and monitoring of performance of decision systems and statistical models Support Leads the design and deployment of enhancements and fixes to systems as needed

Profile: Masters in mathematics, statistics or computer science or related field from a leading university; PhD from an AI lab would be ideal but not a must A minimum 5+ years’ relevant practical experience - conceptual aspects (close to the business) as well as quantitative and qualitative research and analytics expertise In-depth industry/business knowledge in the financial services space (e.g banking, asset management, funds, hedge funds, family offices etc) Solid experience in programming, statistical techniques/modelling, machine learning algorithms and AI The ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets A pragmatic person with strong communication and interpersonal skills, happy being "hands-on/muck-in", at ease in a small structure in a stand-alone role, working closely with the Managing Partner and Investment team Fluent English; any other languages a plus but not a must Already resident in the Geneva area or compelling reasons to move (London might also be an option for this job); you would need to be eligible for a work permit in both cases