Senior Data Scentist
The person filling this position will be part of Experian APAC Data Lab concentrating on novel analytical solutions, new product prototyping, as well as new data asset evaluation and acquisition. This position requires extensive background and knowledge in machine learning and data science.
A successful candidate should also have previous experience in developing machine learning algorithms and/or deep learning based analytic solutions using large datasets. Experience in the areas of optimization, symbolic AI, online marketing, experience in finance, insurance or healthcare is a plus.
The candidate will need to be able to work on multiple concurrent projects, anticipate obstacles, and make high quality deliveries on an aggressive schedule. The candidate must also be a team player that is self-motivated and has excellent communication skills.
Duties and Responsibilities
- 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 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
- Applying, modifying and inventing algorithms to solve challenging business problems
- Developing data driven models to quantify the value of a given data set
- Validating score performance
- Conducting ROI and benefit analysis
- Documenting and presenting model process and model performance
- MS or PhD in Computer Science, Computer Engineering, Mathematics, Statistics or a related field with solid exposure to Machine Learning and/or Advanced Analytics with 3-8 years of applied experience in predictive analytics and exposure to big data analytics
- Strong understanding of the financial or risk domain. Desired domain expertise in Credit Risk, Telecom Analytics, Retail analytics
- 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
- 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