This role is for one of the Weekday's clients

Salary range: Rs 450000 - Rs 550000 (ie INR 4.5-5.5 LPA)

Min Experience: 1 years

JobType: full-time

We are looking for a research-oriented Environmental Data Scientist to spearhead the development of advanced algorithms that improve the accuracy, reliability, and overall performance of air quality sensor data. This role is focused on addressing real-world challenges in environmental sensing, such as sensor drift, cross-interference, and anomalous data behavior — going beyond conventional data science applications.

Requirements

Key Responsibilities:

• Develop and implement algorithms for sensor calibration, signal correction, anomaly detection, and cross-interference mitigation to improve air quality data accuracy and stability.
• Conduct research on sensor behavior and environmental impacts to guide algorithm design.
• Collaborate with software and embedded systems teams to integrate algorithms into cloud and edge environments.
• Analyze large-scale environmental datasets using Python, R, or similar data analysis tools.
• Validate and refine algorithms using both laboratory and field data through iterative testing.
• Create visualization tools and dashboards to interpret sensor behavior and assess algorithm effectiveness.
• Support environmental research initiatives with data-driven statistical analysis.
• Document methodologies, test results, and findings for internal knowledge sharing and system improvement.
• Contribute to team efforts by writing clean, efficient code and assisting in overcoming programming challenges.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Environmental Engineering, Environmental Science, Chemical Engineering, Electronics/Instrumentation Engineering, Computer Science, Data Science, Physics, or Atmospheric Science with a focus on data/sensing.
• 1–2 years of experience working with sensor data or IoT-based environmental monitoring systems.
• Strong background in algorithm development, signal processing, and statistical data analysis.
• Proficiency in Python (e.g., pandas, NumPy, scikit-learn) or R, with experience managing real-world sensor datasets.
• Ability to design and deploy models in cloud-based or embedded environments.
• Strong analytical thinking, problem-solving skills, and effective communication abilities.
• Genuine interest in environmental sustainability and clean technologies.

Preferred Qualifications:

• Familiarity with time-series anomaly detection, signal noise reduction, sensor fusion, or geospatial data processing.
• Exposure to air quality sensor technology, environmental sensor datasets, or dispersion modeling.