Lead Data Scientist

Key Skills

Java Programming, Analytical and Problem solving, Python Programming, Database, SQL, PowerBI, Machine learning techniques, Data Visualization, Natural Language Processing (NLP), NoSQL, NumPy, Pandas, PyTorch, Tableau, TensorFlow, D3.js, Scikit-learn, Natural Language Toolkit - NLTK, R Programming, Shell Scripting language, Linux Operating system

Job Description

• Develop data-driven products from alternative datasets relevant to Capital Market
• Identify new financial market datasets or alternative datasets from vendors that are relevant to Capital Market
• Propose alternative data solutions/products and AI solutions to end users, and oversee the end-to-end implementation
• Implement statistical, machine learning, or mathematical methodologies as needed for specific problems, or data analysis by leveraging alternative data sets
• Lead the development of big data capabilities and utilization, as well as the coordination of cross-functional engineering and analytics initiatives
• Lead innovation and help the business create additional value through the utilization of alternative data assets and analytics
• Identify and monitor key opportunities and the data needs of the business
• Manage and mentor junior data scientists, guide them through the execution of projects, and foster their professional growth 

Front Office

• Proactively identify operational risks/ control deficiencies in the business
• Review and comply with Firm Policies applicable to your business activities
• Escalate operational risk loss events, control deficiencies and risks that you identify to your line manager and the relevant risk and control functions on a timely basis.

What do you need to succeed?

Basic Qualifications (Legislative Requirement)

• Masters or PHD in Mathematics, Statistics, Computer Science, Physics or other quantitative fields.
• 4+ years of experience in Data Science, Machine-Learning, Natural Language Processing or Statistics

Other Required Qualifications:

• Proven track record of solving ambiguous and highly complex problems using data and machine learning
• Proven track of partnership with businesses on leveraging AI products to identify where products can have the most impact on Strong quantitative modelling skills, including statistical modeling, machine learning and optimization
• Ability to perform complex data analysis on large volumes of data and present findings to stakeholders
• Excellent analytical and problem solving skills
• Expert technical documentation skills
• Familiar with a range of data tools
• Work experience with complex visualization of data
• Expert working knowledge of Python, R, and SQL
• Strong coding abilities, preferably in Python using advanced libraries
• Familiar with a Linux environment and shell scripting
• Expert data extract, transform, and load processes with a variety of data types
• Experience with big data technologies –noSQL/SQL databases, parallel processing techniques and Apache Spark

Suggested Qualifications:

• Familiarity with data visualization tools and techniques like D3, R, Qlik, Tableau, PowerBI

  Knowledgeable in standard Python libraries such as pandas, numpy and matlpotlib.

• Knowledgeable in standard ML Python libraries such as scikit-learn, TensorFlow or PyTorch.
• Knowledgeable in NLP Python libraries NLTK, spaCy or huggingface libraries.
• Previous exposure to capital markets
• Good understanding of financial/stock market