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.

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
recruitment@icealion.com
by 26
th
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