Senior Data Scientist
This role is for SEA marketplaces business to support advanced analytics especially in the field of predictive modelling, optimization and coming up with relevant use-cases from the marketplaces data ecosystem.
K ey Responsibilities
- Problem solver with curious mindset with a high execution bias having relevant work experience in Data Science in retail domain.
- Data scientist with hands on expertise in building and executing analytics modules on various technology platforms including big data technology platforms.
- Successful candidates are intellectually curious builders who are biased toward action, scrappy, and communicative.
- Own and complete work streams from business levers, domain know-hows and bias for execution and delivery.
- Be able to compile results from various work streams and be able to make coherent presentations to internal and external stakeholders.
- Experience in building or managing data products, high performer and problem solver.
- Applying best practices to manage solution implementations including code design and reviews
• MS or PhD in Computer Science, Engineering
or a related field with solid exposure to Machine Learning and/or Advanced Analytics with 5+ years of experience in predictive analytics and exposure to big data analytics. MBAs with relevant data science skills will also be considered.
• Strong understanding of the financial domain. Desired domain expertise in credit Risk, telecom analytics, retail analytics. Candidates from Fin-techs preferable.
• Strong coding skills in Python is a must, and in other languages like R and SQL, Hive Sql
• Hands-on experience with Python libraries - NumPy, Pandas, sklearn
• Hands-on knowledge of working with scalable platforms for processing large and/or complex multi-source data sets using Hive, Hadoop or Spark (PySpark) is a plus.
• Comfortable with working on Unix, Windows and databases like Elastic Search and MongoDB
• Demonstrated the use of data optimization (Linear/Non-linear) to solve constrained business problems
• Comfortable with working on Unix, Windows and databases like Elastic Search and MongoDB Must have experience
• Sound knowledge of machine learning concepts. Illustrative machine learning methodologies are:
- Bagging, Boosting, Regularization, Online Learning, One Hot Encoder etc.
- Statistical modeling - CHAID, CART, Regressions, SVM, SVD etc.
- Experience on the text analytics stack - NLP, NLU, LDA, TF-IDF etc.
• Ability to communicate analytics-based insights to business stakeholders. Independent problem solver comfortable to work in an ambiguous solution space. Strong PPT Skills, Excel
• Demonstrated experience in delivering analytics projects in high pressure environments
• Role based in Singapore with 20% travel in APAC