Data Science Manager

Sat Sure is seeking a Data Science Manager interested in building, scaling, and operating geospatial software platforms for agriculture use cases to support state-of-the-art products.
these products need to scale to millions of daily transactions with 99.99% uptime while allowing continuous and rapid deployments across new business lines.
About Sat Sure: Sat Sure is a deep tech, decision intelligence company that works primarily at the nexus of agriculture, infrastructure, and climate action, creating an impact for the other millions, focusing on the developing world.
We want to make insights from Earth observation data accessible to all.
If you are interested in working in an environment that focuses on the impact on society, is driven by cutting-edge technology, and where you will have the freedom to work on innovative ideas and be creative with no hierarchies, Sat Sure is the place for you.
Role: As a Data Science Manager in the Agriculture Domain, your role is pivotal in developing data products, extracting insights, and leveraging decision intelligence to optimize agricultural processes.
This includes tasks such as identifying crop varieties, distinguishing between different agricultural layers, improving crop yields, estimating yields, enhancing sustainability, and driving innovation in the agriculture industry.
You will lead a high-performing team comprising data scientists, ML researchers, and geospatial experts.
Collaboration with cross-functional product and business teams will be crucial 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 central to our mission of supporting and empowering low-income farmers by utilizing geospatial data and ML/DL techniques to facilitate access to agricultural financing.
Data Science Product Development: Lead the development of advanced deep learning, machine learning, and statistical models to address intricate agricultural challenges, including crop classification, yield estimation, and crop disease identification, using remote sensing and geospatial data across various resolutions (high-resolution and low-resolution satellite, drone, and aerial images).
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 & Building Team: Build, Lead, and Manage a team of ML researchers, Data Scientists, and Geospatial and Remote Sensing experts working in the Agriculture domain, 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.
Must-Have: 5 - 8 years of working experience in DL/ML/Data science/Computer Vision.
2+ years of experience in leading a team of data scientists/ machine learning engineers.
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.
Experience in developing advanced computer vision-based deep learning models to tackle complex challenges.
Must have delivered multiple data science product(s) in production.
Bachelor's / Master's degree in Computer Science Engineering, Data Science, Deep Learning / Machine Learning preferred.
Good-to-Have: Experience in developing computer vision-based machine learning and deep learning models for agricultural applications, utilizing remote sensing data.
Experience in leading a team of geospatial engineers to solve challenging problems preferably in the agriculture domain.
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 & experience.
Strong leadership and communication skills.
Ability to work cross-functionally.
Bias for action.
Benefits : Medical Health Cover for you and your family including unlimited online doctor consultations Access to mental health experts for you and your family Dedicated allowances for learning and skill development Comprehensive leave policy with casual leaves, paid leaves, marriage leaves, bereavement leaves Twice a year appraisal Interview Process: Intro call Assessment Presentation Interview rounds (ideally up to 3-4 rounds) Culture Round / HR round

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