We are seeking a highly skilled Data Scientist to collaborate with product design and engineering teams to develop analytical models that drive meaningful business insights. The ideal candidate is passionate about climate conservation and has strong expertise in statistical modeling, data analysis, and machine learning. You will work with large datasets to uncover patterns, optimize processes, and contribute to building scalable analytical solutions. Roles & Responsibilities: Collaborate with product design and engineering teams to develop an understanding of needs Research and devise innovative statistical models for data analysis Enable smarter business processes by using analytics for meaningful insights Keep current with technical and industry developments Experience with Excel, PowerPoint, Tableau, SQL, and programming languages (ex: Java/Python, SAS) Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy Analyze data for trends and patterns, and interpret data with clear objectives in mind Implement analytical models in production by collaborating with software developers and machine-learning engineers. Have a passion for ClimateConservation and build data models for deeper understanding. Skills & Qualifications: Ability to find patterns, trends, and insights from large datasets. Experience in cleaning and validating data for accuracy. Strong problem-solving skills for optimizing models and algorithms. Teamwork and collaboration with product and engineering teams. Strong communication skills to explain insights clearly. Willingness to stay updated with industry trends. Proficiency in Python, R, Java, or SAS for data analysis and modelling. Strong knowledge of SQL for querying and managing data. Experience with tools like Tableau, Power BI, or libraries such as Matplotlib/Seaborn. Hands-on experience in predictive modelling, statistical analysis, and algorithm development. Familiarity with platformslike Hadoop, Spark, AWS, or Azure for handling large datasets.