Domain-Specific Data Scientist (Consultant)

Job Description

Treinetic is seeking a highly skilled and experienced Domain-Specific Data Scientist (Consultant) to contribute to a specialized project focused on environmental data analysis, including air quality, geospatial, and sensor-based datasets. This is a consultation-based opportunity ideal for a senior professional who can apply deep domain expertise in data science to real-world, high-impact challenges.

Responsibilities

• Analyze, clean, and integrate large-scale environmental datasets from sensors, APIs, and GIS platforms.
• Design and implement data warehousing solutions and ETL pipelines to enable efficient storage, processing, and reporting.
• Develop predictive models and analytics to identify environmental trends and support insight generation.
• Collaborate with cross-functional teams including developers, analysts, and environmental experts to ensure data-driven decision-making.
• Ensure compliance with data quality standards and relevant environmental data regulations.
• Contribute to technical documentation and support knowledge sharing across the team.

What We Expect

• Minimum 5 years of professional experience in data science or a related domain, preferably working with environmental, geospatial, or sensor-based datasets.
• Bachelor’s or Master’s degree in Data Science, Environmental Science, Statistics, Computer Science, or a related field.
• Strong proficiency in Python, R, and relevant libraries (e.g., Pandas, NumPy, SciPy).
• Hands-on experience with data warehousing platforms such as Amazon Redshift, Google BigQuery, or Snowflake.
• Deep understanding of air quality indicators (e.g., PM2.5, PM10, CO₂) and scientific data modeling.
• Experience with data visualization tools like Power BI, Plotly, or Tableau.
• Familiarity with API integration, data pipelines, and scientific reporting.
• Excellent analytical thinking and ability to work independently in a consultation capacity.