Pharmaceutical Data Analyst

Placements24; Randburg; Hybrid; ZAR 420,000 - 660,000; Full time

Benefits offered by this job

Hybrid work model

Comprehensive health insurance

Career development opportunities

Job summary

Placements24 is seeking a pharmaceutical Data Analyst to join its analytics team. You will extract, clean, and interpret complex datasets from clinical trials, sales, and market research to drive strategic decisions across R&D, marketing, and sales. This hybrid role offers remote work with on-site collaboration.

You will develop analysis models, create dashboards, monitor KPIs, ensure data integrity and privacy, and communicate insights to technical and non-technical stakeholders.

Qualifications

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, or related quantitative field.
• Proven Data Analyst experience in pharma/healthcare preferred.
• Proficiency with SQL, Python (Pandas, NumX) or R.
• Experience with data visualization tools like Tableau, Power BI, or similar.
• Strong analytical, problem-solving and communication skills.

Responsibilities

• Collect, clean and transform large datasets from clinical trials, sales, and market research.
• Develop and implement data analysis models and statistical techniques to identify trends and insights.
• Create data visualizations, dashboards and reports for technical and non-technical stakeholders.
• Monitor KPIs and provide regular performance updates.
• Collaborate with cross-functional teams to understand data needs and provide analytical support.
• Ensure data integrity and compliance with data privacy regulations.

Skills

Strong analytical skills

Excellent communication

Problem-solving

Education

Bachelor’s or Master’s in quantitative field

Tools

SQL

Python (Pandas, NumX)

R

Tableau/Power BI

Job description

About the Role

Our client is seeking a skilled Pharmaceutical Data Analyst to join their analytics team. This role is pivotal in extracting, analyzing, and interpreting complex datasets related to pharmaceutical research, clinical trials, sales performance, and market trends. You will transform raw data into actionable insights that drive strategic decision-making across various departments, including R&D, marketing, and sales. This hybrid position offers the flexibility to work remotely while also allowing for collaborative sessions with colleagues on-site. Your analytical expertise will be key to uncovering patterns, identifying opportunities, and improving the overall efficiency and effectiveness of the pharmaceutical operations.

Key Responsibilities

• Collect, clean, and transform large datasets from various sources, including clinical trial databases, sales records, and market research reports.


• Develop and implement data analysis models and statistical techniques to identify trends, correlations, and insights.


• Create compelling data visualizations, dashboards, and reports to communicate findings to both technical and non-technical stakeholders.


• Monitor key performance indicators (KPIs) and provide regular performance updates.


• Collaborate with cross-functional teams to understand data needs and provide analytical support.


• Ensure data integrity, accuracy, and compliance with relevant data privacy regulations.

Requirements

• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.


• Proven experience as a Data Analyst, preferably within the pharmaceutical or healthcare industry.


• Proficiency in data analysis tools and programming languages such as SQL, Python (Pandas, NumX), or R.


• Experience with data visualization tools like Tableau, Power BI, or similar.


• Strong analytical, problem-solving, and critical thinking skills.


• Excellent communication and presentation skills, with the ability to explain complex data in a clear and concise manner.

Benefits

• Competitive salary and performance-related bonuses.


• Comprehensive health, dental, and vision insurance.


• Opportunities for continuous learning and professional development in data science and analytics.


• Hybrid work model allowing for a blend of remote and office-based work.


• Access to modern data analytics tools and technologies.