Description

As a Senior Data Science Manager in the Agriculture Domain, you will play a crucial role in building data products, extracting data-driven insights and decision intelligence to optimize agricultural processes such as identifying a variety of crops, discriminating various agri layers, improving crop yields, estimating yields, enhance sustainability, and drive innovation in the agriculture industry. You will lead a high-performing team of data scientists, ML researchers, and Geospatial experts and collaborate closely with cross-functional product and business teams to develop and implement data-driven solutions that address the unique challenges faced by the agriculture sector including the financing of farmer s loans. This role is at the core of the company s mission to support and empower low-income farmers to gain access to Agri financing by leveraging geospatial data and ML/DL techniques. Responsibilities: Data Science Product Development Lead the development of advanced deep learning, machine learning, and statistical models to solve complex agricultural challenges such as crop classification, yield estimation, crop disease identification, etc. using remote sensing and geospatial data. Lead and coach the team to design experiments, develop algorithms, and validate models. Collaborate with stakeholders to understand business objectives and define data science strategies aligned with the goals of the agriculture domain. Also helping with prioritization. Regularly communicate with stakeholders, project managers, and other developers regarding progress on the long-term technology roadmap. Delivering OKRs by defining goals, and roadmaps and facilitating qtr planning, sprint planning, and grooming, retrospective meetings, etc. to achieve those goals. Building, scaling, and automating end-to-end DS solutions to support products at scale. Optimize applications for minimum latency and high scalability Hiring and building a team Build, Lead, and Manage a team of ML researchers, Data Scientists, and Geospatial and Remote Sensing experts providing guidance and mentorship Defining career paths for team members and helping them grow with regular coaching and mentoring. Foster a collaborative and innovative team culture, encouraging knowledge sharing and professional development. Requirement: Must-Have: 8+ years of working experience in DL/ML/Data science preferably from remote sensing or geospatial background. Huge plus if you have agriculture industry knowledge. Experience in leading a team of both data scientist/ machine learning engineers and geospatial engineers to solve challenging problems preferably in the agriculture domain. Statistical knowledge along with great proficiency in Python Strong understanding and implementation experience of predictive modeling algorithms such as regressions, time series, neural networks, clustering, decision trees, and heuristic models, with familiarity dealing with tradeoffs between model performance and business needs Experience combining user research and data science methodologies across multiple products within the business unit. Must have delivered multiple data science product(s) in production. Educational Qualification: Advanced degree (MSc/PhD) in Computer Science, Economics, Engineering, Operations Research, Remote Sensing, Geospatial, Geoinformatics, Physics or Mathematics/Statistics preferred. Competencies: Excellent communication skills that enable you to work cross-functionally with business folks, product managers, and technical experts, building solid relationships with a diverse set of stakeholders. Great at strategic planning, balancing stakeholders, and translating product requirements into technical. Vast analytical problem-solving capabilities and experience. Strong leadership and communication skills. Ability to work cross-functionally. Bias for action.

Role and Responsibilities

• As a Senior Data Science Manager in the Agriculture Domain, you will play a crucial role in building data products, extracting data-driven insights and decision intelligence to optimize agricultural processes such as identifying a variety of crops, discriminating various agri layers, improving crop yields, estimating yields, enhance sustainability, and drive innovation in the agriculture industry. You will lead a high-performing team of data scientists, ML researchers, and Geospatial experts and collaborate closely with cross-functional product and business teams to develop and implement data-driven solutions that address the unique challenges faced by the agriculture sector including the financing of farmer s loans. This role is at the core of the company s mission to support and empower low-income farmers to gain access to Agri financing by leveraging geospatial data and ML/DL techniques. Responsibilities: Data Science Product Development Lead the development of advanced deep learning, machine learning, and statistical models to solve complex agricultural challenges such as crop classification, yield estimation, crop disease identification, etc. using remote sensing and geospatial data. Lead and coach the team to design experiments, develop algorithms, and validate models. Collaborate with stakeholders to understand business objectives and define data science strategies aligned with the goals of the agriculture domain. Also helping with prioritization. Regularly communicate with stakeholders, project managers, and other developers regarding progress on the long-term technology roadmap. Delivering OKRs by defining goals, and roadmaps and facilitating qtr planning, sprint planning, and grooming, retrospective meetings, etc. to achieve those goals. Building, scaling, and automating end-to-end DS solutions to support products at scale. Optimize applications for minimum latency and high scalability Hiring and building a team Build, Lead, and Manage a team of ML researchers, Data Scientists, and Geospatial and Remote Sensing experts providing guidance and mentorship Defining career paths for team members and helping them grow with regular coaching and mentoring. Foster a collaborative and innovative team culture, encouraging knowledge sharing and professional development. Requirement: Must-Have: 8+ years of working experience in DL/ML/Data science preferably from remote sensing or geospatial background. Huge plus if you have agriculture industry knowledge. Experience in leading a team of both data scientist/ machine learning engineers and geospatial engineers to solve challenging problems preferably in the agriculture domain. Statistical knowledge along with great proficiency in Python Strong understanding and implementation experience of predictive modeling algorithms such as regressions, time series, neural networks, clustering, decision trees, and heuristic models, with familiarity dealing with tradeoffs between model performance and business needs Experience combining user research and data science methodologies across multiple products within the business unit. Must have delivered multiple data science product(s) in production. Educational Qualification: Advanced degree (MSc/PhD) in Computer Science, Economics, Engineering, Operations Research, Remote Sensing, Geospatial, Geoinformatics, Physics or Mathematics/Statistics preferred. Competencies: Excellent communication skills that enable you to work cross-functionally with business folks, product managers, and technical experts, building solid relationships with a diverse set of stakeholders. Great at strategic planning, balancing stakeholders, and translating product requirements into technical. Vast analytical problem-solving capabilities and experience. Strong leadership and communication skills. Ability to work cross-functionally. Bias for action.