DS Capabilities
- Banking or financial industry experience
- Tertiary qualified and experience working as a data scientist or analytics/modelling role
- Industry experience in machine learning model development and pipeline, tuning and deployment. (e.g. time series prediction, classification and segmentation etc.)
- Experience in creating advanced analytics modelling (e.g. supervised/unsupervised machine learning) and its use in business contexts
- Solid understanding in underlying statistic and mathematic theory behind model used. (Strong understanding in anomaly detection, NLP (BERT) are favourable.)
- Strong programming experience with Python/ R and SQL with the ability to articulate and demonstrate good coding practices
- Experience working with large amount of data
- Able to deliver consistent and accurate and repeatable analysis. Presenting current trends and emerging issues to key stakeholders
- Experience of building solution from scratch & effective deployment of models on the specified ecosystem with examples of improved performance, productivity, decision making and/or automation
- Ability to work independently and as a part of a team to drive initiatives in an agile delivery environment
- Strong communication and presentation skills to translate analysis into insights and present findings
Soft skills:
- Story -Telling
- Team player
- Proactive
- Problem-solving
Technical tool kit:
- Python
- Strong SQL on SQL Server or Teradata
- Deep statistical understanding and affinity for or experience with statistical and mathematical methods of data analysis (e.g., SVM, DBSCAN, text mining)
- Cloudera / Spark/PYSPARK
DESIRED EXP. / COMPA COST:
Mid to Sr level DS with minimum 3 years of relevant experience
