Data Science Analyst

Department: Project Services

Employment Type: Permanent - Full Time

Location: Manila

Data Science Analysts investigate, develop, implement, and deploy a range of statistical and predictive solutions to benefit our clients in a variety of industries to help them answer their business challenges. In addition to the execution of various projects, this role also acts as an analytics consultant to both internal project teams and clients by translating data analysis and modeling into tactical and strategic insights that are clear, accurate, understandable, and applicable to decision making.

This is done using an array of tools, techniques, and frameworks that vary depending on the type of analysis being conducted. The four major types of analytics include: descriptive analytics (looks at data to examine, understand, and describe something that’s already happened), diagnostic analytics (goes deeper than descriptive analytics by seeking to understand the why behind what happened), predictive analytics (relies on historical data, past trends, and assumptions to answer questions about what will happen in the future), prescriptive analytics (aims to identify specific actions that an individual or organization should take to reach future targets).

Advanced statistical analysis

• Responsible for mining large data sets, executing statistical modeling and machine learning techniques, leading data interpretation and visualization of results to deliver insights
• Responsible for executing a variety of analyses such as: cluster analysis/segmentation, text analytics, customer lifetime value modeling, retention and survival models, portfolio analysis, propensity modeling, database scoring, clickstream data analysis, etc.
• Ensure that the method and analysis connect with the business challenge and overall project goals. Translate analysis into tactical and strategic insights
• Confidently guide clients and colleagues in understanding the insights derived from statistics and predictive techniques
• Skilled with data science programming in Python and SQL
• Stay up to date with emerging analytical techniques, demonstrating the ability to implement fresh thinking to create new value

Data handling

• An expert in using common technical tools to make the analyses / reporting more efficient through advanced usage of them (e.g., macros, syntaxes, etc.).
• Can organize any dataset in a usable format.
• Can design and implement automation on customized and complex trackers to ensure efficiency.
• Collaborate with seniors & experts to apply new technical skills (e.g., programming in different languages, developing new algorithms), techniques to accelerate computing and processing power of big data.

Data quality assurance

• Can propose out of the box solutions for any dataset.
• Collaborate with expert data engineers to correct data quality errors and enhance the data collection process.

Reporting & Visualization

• Can effectively communicate trends, patterns, and predictions based on relevant findings.

Account management

• Help in defining priorities for improving project execution on recurring accounts, either on ad hoc or structural projects (e.g., identify possibility to automate implementation, strengthen partnership with 3rd parties, etc.).

Method management

• Develop automation scripts for frequently implemented data processing and / or analysis techniques, that can be used cross projects.
• Collaborate with experts across departments in optimizing research methodologies and approaches.
• Can document innovation / new ways of conducting analysis.
• Can develop norms and processes to maintain it.

Technical knowledge

• An expert in all analytical and reporting software used.
• Has intermediate understanding and application of programming languages such as R, Python, Scala, Java, SQL, Julia, MATLAB.

Market Research Knowledge

• Has extensive market research knowledge and share expertise.
• Stay up to date with the industry trends and apply changes in own work.
• Share learnings within the team related to market research.

Marketing knowledge

• Has a genuine interest in marketing and brands.
• Has a basic understanding of the importance of marketing for organizations.

Language knowledge

Manage English at a professional level (verbal/ writing) and able to have a fluent and accurate conversation.

• Bachelor’s or Master’s degree in Statistics, Data Sciences, Economics, Operations Research, Applied Mathematics, Computer Science, or related field of study is desirable
• 4+ years of experience in data science and advanced modeling (such as statistical, econometric, optimization, machine/deep learning)