What are the skills required?

Machine learning is the subfield of computer science that, according to Arthur Samuel, gives "computers the ability to learn without being explicitly programmed." Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term "machine learning" in 1959 while at IBM. Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions, through building a model from sample inputs.

Python is a widely used high-level programming language for general-purpose programming, created by Guido van Rossum and first released in 1991.

SQL ( ESS-kew-EL or SEE-kwl, Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS).

Ability to deconstruct information into smaller categories in order to draw conclusions

The ability to communicate effectively with superiors, colleagues, and staff is essential, no matter what industry you work in.

Data analysis, also known as analysis of data or data analytics, is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.

Data visualization or data visualisation is viewed by many disciplines as a modern equivalent of visual communication.

Able to speak English

Able to speak Mandarin

In computer programming, pandas is a software library written for the Python programming language for data manipulation and analysis.

Experience performing creative and systematic work to understand a product, market, or customer, either before building a new solution, or to troubleshoot an existing issue

The ability to collect and analyze information, problem-solve, and make decisions

Data integration involves combining data residing in different sources and providing users with a unified view of them.

Working experience of Data Transformation, which is the process of converting data from one format or structure into another format or structure.

In computer science, data validation is the process of ensuring that a program operates on clean, correct and useful data.

Working experience of Data wrangling, which is the process of transforming and mapping data from one raw data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics.

Planning (also called forethought) is the process of thinking about and organizing the activities required to achieve a desired goal.

Predictive analytics encompasses a variety of statistical techniques from predictive modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events.

Able to speak Bahasa Malaysia

Working experience of BigQuery, which is a RESTful web service that enables interactive analysis of massively large datasets working in conjunction with Google Storage. It is an Infrastructure as a Service (IaaS) that may be used complementarily with MapReduce. BigQuery provides an external access to the Dremel technology, a scalable, interactive ad hoc query system for analysis of read-only nested data.

Experience identifying business needs and and determining solutions to business problems.

Working experience of Data Archiving, which is the process of moving data that is no longer actively used to a separate storage device for long-term retention. Archive data consists of older data that is still important to the organization and may be needed for future reference, as well as data that must be retained for regulatory compliance. Data archives are indexed and have search capabilities so files and parts of files can be easily located and retrieved.

Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data.

Working experience of Data Entry. Data entry is the professional term for entering information into a computer or data-recording system using an electronic or mechanical device.

Data management comprises all the disciplines related to managing data as a valuable resource.

Data manipulationis the process of changing data in an effort to make it easier to read or be more organized.

Data mining is the computing process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques.

Data modeling is the process of creating a data model for the data to be stored in a Database.

In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis, and is considered a core component of business intelligence.

Database management refers to the actions a business takes to manipulate and control data to meet necessary conditions throughout the entire data lifecycle.

In psychology, decision-making is regarded as the cognitive process resulting in the selection of a belief or a course of action among several alternative possibilities.

Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends.

Working experience of Regression Analysis, which is a set of statistical processes for estimating the relationships among variables.

a simplified, mathematically-formalized way to approximate reality (i.e. what generates your data) and optionally to make predictions from this approximation. The statistical model is the mathematical equation that is used.

.NET Framework (pronounced dot net) is a software framework developed by Microsoft that runs primarily on Microsoft Windows.

Data base management system software

Data base management system software

Working experience of Attribution Analysis, which is a performance-evaluation tool used to analyze the ability of portfolio and fund managers. Attribution analysis uncovers the impact of the manager's investment decisions with regard to overall investment policy, asset allocation, security selection and activity.

Working experience of Big Data Analytics, which refers to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from big data - data sets that are so voluminous and complex that traditional data-processing application software are inadequate to deal with them.

Business Intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis of business information.

Apache Cassandra is a free and open-source distributed NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.

Working experience of Change data capture. In databases, change data capture (CDC) is a set of software design patterns used to determine (and track) the data that has changed so that action can be taken using the changed data.

Integration of information from multiple applications, created and maintained by organisations, into one consistent and transparent data structure

Data acquisition is the process of sampling signals that measure real world physical conditions and converting the resulting samples into digital numeric values that can be manipulated by a computer.

In information technology, data architecture is composed of models, policies, rules or standards that govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and in organizations.

Data conversion is the conversion of computer data from one format to another.

Working experience of Data Engineering, which includes gathering and collectiong of data, storing it, batch processing or real-time processing of data, and setting up access via e.g. an API.