Position : Environmental Data Scientist
Salary: upto 50000 pm
Location: Ahmedabad [Only preferring candidates from Gujarat]
Experience: 2+ Years
we are seeking a research-driven Environmental Data Scientist to lead the
development of advanced algorithms that enhance the accuracy, reliability, and
performance of air quality sensor data. This role goes beyond traditional data science
— it focuses on solving real-world challenges in environmental sensing, such as
sensor drift, cross-interference, and data anomalies.
Key Responsibilities:
- Design and implement algorithms to improve the accuracy, stability, and interpretability of air quality sensor data (e.g., calibration, anomaly detection, cross-interference mitigation, and signal correction)
- Conduct in-depth research on sensor behavior and environmental impact to
- inform algorithm development
- Collaborate with software and embedded systems teams to integrate these
- algorithms into cloud or edge-based systems
- Analyze large, complex environmental datasets using Python, R, or similar
- tools
- Continuously validate algorithm performance using lab and field data; iterate
- for improvement
- Develop tools and dashboards to visualize sensor behavior and algorithm
- impact
- Assist in environmental research projects with statistical analysis and data
- interpretation
- Document algorithm design, testing procedures, and research findings for
- internal use and knowledge sharing
- Support team members with data-driven insights and code-level
- contributions as needed
- Assist other team members with writing efficient code and overcoming
- programming challenges
Education/Experience
Required Skills & Qualifications
- Bachelor's or Master's degree in one of the following fields: Environmental Engineering / Science, Chemical Engineering, Electronics / Instrumentation Engineering, Computer Science / Data Science, Physics / Atmospheric Science (with data or sensing background)
- 1-2 years of hands-on experience working with sensor data or IoT-based environmental monitoring systems
- Strong knowledge of algorithm development, signal processing, and statistical
- analysis
- Proficiency in Python (pandas, NumPy, scikit-learn, etc.) or R, with experience
- handling real-world sensor datasets
- Ability to design and deploy models in a cloud or embedded environment.
- Excellent problem-solving and communication skills.
- Passion for environmental sustainability and clean-tech.
Preferred Qualifications:
- Familiarity with time-series anomaly detection, sensor fusion, signal noise reduction techniques or geospatial data processing.
- Exposure to air quality sensor technologies, environmental sensor datasets, or dispersion modeling.
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