Koïos Intelligence Inc., established in 2017, is the realization of the vision of an experienced and multidisciplinary team coming from a wide range of scientific, academic and professional backgrounds. Powered by machine learning, operations research and business analytics, Koïos delivers personalized solutions that create a synergy around in-house client systems. In this role, the candidate will work with a multidisciplinary team to design, develop & create analytical solutions through applications of Data Mining, Machine Learning. The ideal candidate will help the team to develop ML applications and take advantage of emerging technologies around Data Science. The candidate will be expected to be hands-on as well as guide and mentor new modellers in the team.
- Understand business needs and apply Machine Learning/Big Data technology to solve real-world business problems
- Ability to build and optimize models using machine learning techniques including features selection & engineering
- Address pain points of the business and provide additional insights across domains like Regression, Classification, Machine Vision, Natural Language Processing, Deep Learning, reinforcement learning and/or statistical modelling
- Implement the modern framework of CNN, RNN and LSTMs on the software in production
- As a technical lead candidate, you will be working with various team members such as data engineers, data scientists, statisticians, actuaries and with application developers
- Analyze source data, working with structured and unstructured data
- Manipulate high-volume, high-dimensionality data from varying sources to highlight patterns, anomalies, relationships, and trends
- Extend the company’s data with third-party sources of information when needed
May manage one or more advanced research projects simultaneously
- Present analysis and recommendations to the target audience
MSc (Science, Technology, Engineering, Mathematics) degree with 2 years of experience. Moderate working knowledge of modelling/research/analytics or actuarial required. Relevant statistical analysis work experience required.
Education, Work Experience & Knowledge
Relevant work experience in research and/or advanced analytic work (e.g. predictive modelling) in the insurance industry preferred.
Job Specific & Technical Skills & Competencies
Computer Proficiency: Ability to read/revise/review a statistical software program (e.g. Python, R, Java, C++ an advantage) Ability to create advanced programs from scratch. Leading the Business: Problem Solving & Decision Making. Risk Taking, Innovation. Results Orientation. Business Perspective. Seeks Opportunities to Learn. Business Acumen: Understanding and knowledge of key business knowledge areas (e.g. product, enterprise, industry, claim process and competitors). Ability to leverage business knowledge to determine approaches to execution. Critical Thinking: Ability to take action in solving problems while exhibiting judgment and a realistic
Statistics: Understanding of advanced statistics underlying data models. Ability to apply new statistical procedures to work. Demonstrates strong ability and knowledge of database principles, data profiling, statistics and data modelling and can apply this knowledge in new or complex situations.
2+ years of experience in one or more of the following: Machine Learning Libraries, TensorFlow, Machine Vision, and Natural Language Processing
4+ years of experience in programming with Python, R, C++ or Java
1+ years of experience in handling data and working with database tools, e.g., SQL, NoSQL, MongoDB, Hadoop or Spark
Proven ability to work creatively and analytically in a problem-solving environment
Excellent communication (written and oral) and interpersonal skills
Experience with contributing to open source project