At Pulsifi, we believe that there is a pulse to each person that defines who we are, what we are good at, and what we can become. We help people and organizations realize their pulse. 

Pulsifi is a HR technology company creating a People Data Platform, the next generation decision platform for recruitment and talent management. Combining HR best practices with artificial intelligence, we develop deep predictive actionable insights into people and organizations in ways not possible before, creating new golden standards for HR practitioners globally.

Pulsifi is founded and led by experienced professionals from the technology and HR industries, and the team is currently based across Kuala Lumpur and Singapore. 

We are looking for a talented, self-driven, and passionate Data Analyst to join our team in Kuala Lumpur, Malaysia. This role will report into our Lead Data Scientist. Everything we do is predicated on having a great team and a culture of continuous learning

We are looking for Data Analyst who has:

• The ability to work effectively with cross-functional teams, including data scientists and data engineers, to understand data requirements and collaborate on data projects.
• Strong verbal and written communication skills to convey complex data insights to non-technical stakeholders in a clear and concise manner.
• A keen eye for detail to ensure data accuracy, integrity, and quality in all analysis and reporting activities.
• Strong analytical skills to analyze data, identify patterns, and draw meaningful conclusions to support decision-making processes related to machine learning model improvements.
• The ability to identify data-related challenges and develop solutions to address them, including data optimizations, model enhancements, and business strategies.
• The ability to adapt to changing data requirements, technologies, and business needs in a dynamic and fast-paced environment.

What you will do: 

• Analyze client's data using tools such as SQL, Python, and other data analytic platforms (e.g., BigQuery) to identify patterns, trends, and correlations. You will apply statistical techniques to interpret and summarize data, create visualizations, and generate reports to communicate findings to stakeholders.
• Clean, validate, and transform raw data into usable formats for analysis. This may involve data extraction, data integration, and data quality assessment to ensure data accuracy and integrity.
• Create data models and visualizations to represent complex data sets in a simplified manner. This may include creating dashboards, charts, and graphs using data analytic platforms or libraries (e.g., pandas, matplotlib, seaborn) to visualize data insights and trends for stakeholders.
• Provide insights and recommendations based on data analysis to support decision-making processes related to machine learning model improvements. You will collaborate with data scientists and data engineers to identify opportunities for data-driven optimizations, model enhancements, and business strategies.
• Work closely with data scientists and data engineers to understand data requirements, data pipelines, and data integration processes. You will collaborate on data projects, contribute to data-related discussions, and provide input on data strategies and best practices.
• Adhere to data governance policies, standards, and procedures to ensure data security, privacy, and compliance. You will also participate in data audits and reviews to ensure data accuracy, integrity, and quality
• Work in accordance with applicable policies, processes, and procedures constituting Pulsifi’s Information Security Management System (ISMS). This includes but is not limited to the organization’s Information Security Policy, Data Protection Policy, Clean Desk & Screen Policy & Password Management Policy. 

You meet all or most of these requirements: 

• Preferred Bachelor’s Degree in Business Analytics or Statistics.
• Proficient in SQL for data querying and manipulation, Python for data analysis, visualization, and automation, and experience with data analytic platforms such as BigQuery or similar tools.
• Experience with data analysis and visualization tools such as pandas, matplotlib, seaborn, or similar libraries for creating interactive dashboards and visualizations.
• Familiarity with statistical techniques such as hypothesis testing, regression analysis, and data modeling to interpret data and derive meaningful insights.
• Experience in cleaning, validating, and transforming data into usable formats for analysis.