Principal Analytics Professional

5 days ago

Bharatpur, Rajasthan, India beBeeDataScience Full time ₹ 20,00,000 - ₹ 25,00,000
Job Title

We are seeking a highly motivated Data Scientist to drive advanced analytics initiatives across the organization.

About the Role
  • Lead end-to-end analytics projects, encompassing data wrangling, model development, validation, and deployment.
  • Collaborate with scientific and operational teams to identify opportunities for data science applications in drug discovery, development, and manufacturing.
  • Interact with domain experts and clients to understand data, business challenges, and implement robust, scalable solutions.
  • Design and implement machine learning models, statistical analyses, and data visualizations to solve real-world problems.
  • Develop predictive models for reaction outcomes, process optimization, and quality control.
  • Work with structured and unstructured data from lab equipment, sensors, and other scientific instruments, as well as enterprise applications (CRM, ERP, etc.).
  • Build and maintain data pipelines and dashboards for real-time monitoring and reporting.
  • Implement AI workflows to enhance decision-making processes.
Qualifications
  • Education: MS/MTech in Mathematics, Statistics, Computer Science.
  • Experience: 3+ years in data science or advanced analytics.
  • Proficiency in Python, R, SQL, and data visualization tools (e.g., Power BI, Tableau).
  • Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
  • Familiarity with cheminformatics or bioinformatics tools (e.g., RDKit, KNIME) is beneficial.
  • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
Desirable Skills & Expertise
  • Solid understanding of statistical and machine learning algorithms and applications.
  • Expertise in using Python for machine learning and complex data analysis.
  • Experience with cloud platforms (AWS, Azure, GCP).
  • Knowledge of FAIR data principles and data governance in scientific environments.
  • Exposure to digital lab tools like ELN, LIMS, or CDS.
  • Understanding of regulatory requirements in pharma (e.g., GxP, 21 CFR Part 11).
  • Knowledge of Computer Vision and Gen AI approaches.
  • Excellent storytelling and presentation skills.
  • Ability to work in a dynamic multidisciplinary environment.

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