As a Data Scientist – Asset Management in the ICEA LION Data Analytics Team, you will work closely with investment and data professionals across ICEA LION Asset Management to proactively source, due diligence and draw insights from in-house investment and alternative data. The role will help develop and drive innovative solutions for amplifying data-driven investment decision-making, improved client engagement, and operational effectiveness. This role will assist in all phases of project work, including problem identification, formulation, model development, and deployment.

Key Responsibilities

• Work with portfolio managers to understand sources of alpha and opportunities to improve decision-making process
• Build tools and systems to understand decision data, context and events around it to enhance ICEA LION Asset Management’s decision attribution capabilities and systematically identify opportunities
• Work with partners in technology and user experience to build out tools providing real-time insights to portfolio managers and their teams
• Take part in projects along the full data science spectrum. From data acquisition and wrangling, to model selection to presentation and data visualization.
• Analyze and visualize diverse sources of data, interpret results in a business context and report results clearly and concisely
• Work collaboratively with different business partners and be able to present results in a clear and concise manner
• Assist with developing and deploying educational workshops/seminar series for staff to accelerate data maturity.
• Communicate results/findings; draft and edit scientific abstracts, presentations, and journal articles.
• Present work at workshops, seminars, and conference proceedings within and outside of the company.

If you match the qualifications and experienced of any of the jobs here, submit your CV quoting the job title on the subject line to [email protected] by 26th April 2024.

Requirements

• Bachelor’s degree in Actuarial Science, Computer Science, Data Science, Engineering, Statistics, Economics, Mathematics, Business or Physics
• Master’s degree and professional qualifications will be added advantage.
• Qualified or Nearly Qualified CFA will be added advantage
• 1-3 years relevant experience in Financial Services
• Prior experience working in alpha capture, performance attribution or trading / decision analytics role will be added advantage
• Strong analytical/modelling skills and business orientation with proven ability to use data and analytics to drive business results; strong technical background
• Demonstrate solid experience working within a data team, including Time series analysis and modelling; Training and fine-tuning of the Machine Learning model for investment models; Strong knowledge of Python for data scientists (e.g., pandas), traditional Machine Learning and deep learning libraries (e.g., scikit learn, xgboost, TensorFlow, Torch, etc.); Data manipulation languages (e.g., SQL); Data visualization / presentation skills (e.g., Tableau, PowerBI and DOMO)
• Demonstrate experience working with engineering, developers and other technology teams – Writing production quality code, unit testing and familiarity with version control; Familiar with cloud-based technologies.
• Strong communications skills (both verbal and written) and the ability to present findings to a non-technical audience
• Passion for learning and adopting a wide range of techniques in an agile environment