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.