Systems Engineer (Data Visualisation)

Bahwan CyberTek; Mumbai; On-site; INR 800,000 - 1,200,000; Full time

Job summary

A leading pharmaceutical company is looking for a highly skilled Data Visualization Engineer in Mumbai. The ideal candidate will create innovative visualizations, collaborate across teams, and maintain visualization tools. They should hold a degree in Computer Science or Data Science and have experience with tools like Tableau and Power BI. This role is vital for translating complex data sets into compelling narratives that drive decision-making in drug discovery and development.

Qualifications

• Education in a relevant field like Computer Science or Data Science.
• Experience in pharmaceutical or biotech sectors preferred.
• Proficient in various data visualization tools.

Responsibilities

• Create interactive and static visualizations for data analyses.
• Develop dashboards to summarize insights from R&D datasets.
• Collaborate with scientists to identify visualization needs.
• Integrate and structure datasets for visualization purposes.

Skills

Data visualization

Storytelling ability

Analytical thinking

Effective communication

Education

Bachelor's or Master’s degree in Computer Science, Data Science, or Bioinformatics

Tools

Tableau

Power BI

SQL

Pandas

D3.js

PyMOL

Job description

highly skilled and innovative Data Visualization Engineer to join our pharmaceutical R&D team. The ideal candidate will have a strong background in data science, advanced visualization techniques, and expertise in tools and technologies for creating insightful and interactive visualizations across various data types. The role requires close collaboration with scientists, analysts, and other stakeholders to translate complex datasets into impactful visual narratives that drive decision-making in drug discovery, development, and clinical research.

POSITION RESPONSIBILITIES

Design and Develop Visualizations

• Create interactive and static visualizations for exploratory, descriptive, comparative, and predictive analyses.
• Develop dashboards and reports for summarizing key insights from high-throughput screening, clinical trial data, and other R&D datasets.
• Implement visual representations for pathway analysis, pharmacokinetics, omics data, and time-series trends.

Collaborate with Cross-Functional Teams

• Partner with data scientists, bioinformaticians, pharmacologists, and clinical researchers to identify visualization needs.
• Translate complex scientific data into clear, compelling, and actionable visual insights tailored to technical and non-technical audiences.

Maintain and Optimize Visualization Tools

• Build reusable visualization components and frameworks to support large-scale data analysis.
• Evaluate and recommend tools and platforms for effective data visualization, including emerging technologies.

Data Processing and Integration

• Collaborate with data engineers to integrate, clean, and structure datasets for visualization purposes.
• Ensure alignment of visualization solutions with pharmaceutical R&D standards, compliance, and security requirements.

Innovation and Expertise Development

• Stay updated on the latest trends in visualization technology and methods relevant to pharmaceutical research.
• Apply advanced techniques like 3D molecular visualization, network graphs, and predictive modeling visuals.

EDUCATION AND EXPERIENCE

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Bioinformatics, or a related field.
• Experience in pharmaceutical or biotech sectors is a strong plus.

TECHNICAL SKILLS REQUIREMENTS

• Visualization Tools: Expertise in Tableau, Power BI, Plotly, ggplot2, Matplotlib, Seaborn, D3.js, or equivalent.
• Data Handling: Experience with SQL, Pandas, NumPy, and ETL processes.
• Omics and Network Tools: Familiarity with Cytoscape, BioRender, or molecular visualization platforms (e.g., PyMOL, Chimera).
• Dashboarding: Building interactive dashboards with Dash, Shiny, or Streamlit.
• 3D Visualization: Experience with tools for structural and spatial visualization (e.g., PyMOL, PyVista).
• Strong storytelling ability to convey scientific insights visually.
• Effective communication and collaboration with interdisciplinary teams.
• Analytical thinking to align visualizations with research goals.