M08 - Data Scientist

Responsibilities

• To use Python/R or other tools to generate Monthly draft billing statement (overall and by agencies) based on source inputs and business rules
• To use Python/R or other tools to process source inputs and business rules and visualise on PowerBI Monthly contact center reports for vendor performance as well as provide scorecard
• Facilitate discussions with stakeholders to understand their business challenges, sharpen the business use cases and translate them into data science projects
• Perform data cleaning, pre-processing, feature engineering, and build data science models to address the use case
• Identify data quality issues from source inputs and propose changes that can help to reduce these occurrences
• Present findings, solicit feedback and prioritise refinements to the analysis in close iteration with stakeholders while managing overall project timeline
• Communicate the data insights in a clear and compelling narrative, supported with impactful visuals, to influence key decision makers

• Depending on the use case, design of dashboards and interactive visualisations as tools for data exploration and storytelling may be expected

Experience and Skills requirement

• Capable of translating business use cases into analytical problems, and identifying appropriate data sources to tackle these problems.
• Proficient in writing scripts in R/Python for data preparation and analysis, using modern analysis tools & programming methodologies.
• Proficient cleaning, imputing and correcting anomalies in the collected structured or unstructured data to ensure a high standard of quality in data sets to be used in the analysis work.
• Proficient in exploring and analysing datasets, applying probability and statistical methodologies and techniques to discover insights from the data.
• Proficient in building machine learning models to identify, recognise patterns and make predictions.
• Proficient in design principles and use of visualisations to best convey the intended information.
• Capable of developing data visualisation from standalone graphs and charts on to highly customised tools and apps while tightly integrated to the data systems for real time visualisation of information.
• Capable of translating results from analysis work into actionable recommendations for stakeholders.
• Capable of communicating results from analysis work in a coherent data story for stakeholders.
• Experience in model deployment.
• Experience in stakeholder management.
• Experience in agile project management.