Data Scientist - Digital Transformation - Agri

Data Scientist - Digital Transformation

- My Client was founded almost 20 years ago with a focus on creating - prolific, commercially successful breeding programs. They started with vegetables seeds and achieved market leadership in Okra and Tomato. They entered field crops business with the introduction of a hybrid rice variety in 2006 and entered BT cotton in 2011.

- They grew the vegetable seeds business into India's largest domestic breeding program (~ INR 150 cr in sales). In June 2015,

- The field crops business delivered ~ INR 150 cr of revenues in YE June 2016. About 10% of revenues come from exports of hybrid rice to South East Asia. They also have a biotech facility in Singapore and rep offices/100% subs in Philippines.

Required Skills :

- Bachelor's degree in Statistics, Mathematics, Computer Science, or any quantitative field.

- R/Python Programming Skills, Statistics, Multivariable Calculus & Linear Algebra, Data Wrangling, Data Visualization & Communication, Software Engineering and Data Intuition.

- Exposure to algorithms like Linear Regression, Logistic Regression, Time Series Forecasting, Clustering, Decision Tree and understanding of Neural Networks, Machine/Deep Learning, NLP and their Business Applications

- Must have had at least 3 years of experience working with business analysis/informatics and business outcomes research within a fast-paced and complex business setting.

- Ability to work effectively in a group/collaborative setting, be result oriented, be highly analytical, be a strategic and creative thinker

- Have superior organizational skills, have a strong attention to details, have an ability to work on multiple projects and meet tight deadlines

- Have exceptional problem-solving skills and remain calm and composed in times of stress and uncertainty.

Responsibilities :

- Develop a long-term holistic data acquisition and analytics strategy.

- Work with stakeholders to determine use business data for valuable business solutions

- Search for ways to get new data sources and assess their accuracy.

- Browse and analyse enterprise databases to simplify and improve product development, marketing techniques, and business processes

- Create custom data models and algorithms

- Use predictive models to improve customer experience, ad targeting, revenue generation

- Develop the organization's test model quality and A/B testing framework

- Coordinate with various technical/functional teams to implement models, monitor results

- Develop processes, techniques, and tools to analyse and monitor model performance while ensuring data accuracy

- Build his team to enhance the business analytics operations in the Company