Junior Data Scientist

Upskills provides expert financial software consulting for investment banks and leading financial institutions in Asia Pacific, Middle East and Europe region. With a strong, Front to Back expertise of cash and derivatives markets, coupled by an in-depth knowledge of financial markets technologies, we provide smart, business-wise, and efficient solutions.
We are seeking for a highly-motivated Data Scientist that will help discover information hidden in vast amounts
of data to make smarter decisions that would help our banking client. You will
be applying data mining techniques, doing statistical analysis, and building
high quality prediction systems integrated with our products. Looking to
automate scoring using machine learning techniques, build recommendation
systems, develop internal A/B testing procedures for Sales campaigns Selecting
features, building and optimizing classifiers using machine learning techniques. 

• Work with Data Scientist and
  product management to implement data-driven features/product. 
• Apply architecture and system
  design theories and principles, perform complex work in research, design,
  and development of new or existing products, tools and processes required for
  the operation, maintenance and testing of products.
• Create data tools for analytics
  and data scientist team members that assist them in building and
  optimizing our product into an innovative industry leader.
• Try out anomaly detection models. 
• Be a key contributor in the
  engineering of distributed systems, frameworks, and design patterns of
  Data Science/Machine Learning. 
• Use Scala, Java or Python to
  utilize Hadoop/Spark to collect and analyse large-scale datasets in batch and real-time. 
• Build, monitor, and maintain data
  ETL pipelines. 

Requirements

• Master’s or Bachelor’s Degree in Data Analytics, Machine Learning, Computer Science or Quantitative
  discipline. 
• Leadership in generating ideas.
• Undertaking data collection, preprocessing and
  analysis of structured and unstructured data. 
• Proficient in Programming Languages, such as Python, R. 
• Experience with data visualization tools such as
  Tableau, Qlikview, GGPlot etc…
• Good applied statistics skills, such as distributions,
  statistical testing, regression.
• Knowledge about Financial Products and Process in Capital Markets industry are strong plus.
• Experienced in using Big Data Architecture and the tools in the landscape. 
• Strong theoretical foundation in Statistics, and Advanced Machine Learning concepts. 
• Experienced in Development of NLP based Deep Learning Models and Recommendation models as well.