Senior Data Analyst/ Data Scientist
About the Role
A member of the squad who is responsible for delivering business value from data. They achieve this by analysing data, presenting data insights and reports with business application, developing data led improvements to products, translating business needs and requirements into predictive analysis, functionalities and software specifications, driving true value to our customers; bridging the gaps between business, data and delivery teams. What to expect
What will make you successful? Professional and Technical Skills
- Work as part of an agile team towards providing quality findings through data and analysis.
- Utilise programming skill such as Python and SQL in designing analysis and statistical models.
- Engage stakeholders and agile team members as data champion in guiding and leading work related to data science and analysis.
- Build knowledge bank within the team with insight and intel of the banking, financial and technology industry.
- Excellent verbal and written communications
- Proven experience in using multiple data science methodologies in solving complex business problems - analytical mind and business acumen
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
- Strong understanding and background in applying statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Experience in applying one or more AI/ML libraries: PyTorch, Keras, Tensorflow, Prophet, scikit-learning, etc.
- Adept at data manipulation and processing tools: Python (generic, Numpy, Pandas), R, SQL, Hadoop stack, Spark
- Good understanding of big data technologies: NoSQL, MapReduce, stream and batch processing, Dataflow model, Kafka
- Familiar with data visualization stack: Tableau, Microstrategy, ggplot2, D3, matplotlib, Seaborn
- Experience in deploying solution to production and comfortable with DevOps, MLOps, CI/CD, API practices.
- 5-7 years of experience in data analytic/science.
- Bachelor in Computer Science, Engineering (quantitative), Mathematics, Physics, Statistics, or a quantitative field. Candidate with Master qualifications or research experience a strong plus.
- Applicable research experience.
- Strong background in one or more area: time-series analysis, NLP, product analytic, risk analytic, fraud detection, anomaly detection.
- Comfortable with vast datasets and ability to reveal insights from data fast.
- Experience in Agile methodology.