
Data Scientist
3 weeks ago
- The Data Scientist will utilize data science techniques to solve real-world problems to enable informed decisions to Crop Protection Development (CPD) and related divisions.
- While partnering with other data scientists, developers, domain experts, product managers and other stakeholders Data Scientist will build various data science solutions by collecting, analysing, and interpreting large datasets, building algorithms and predictive models.
- Will contribute to the development and enhancement of customer (farmer/grower) centric mobile application.
Accountabilities
With a focus on the Digital and Data Science critical initiatives for Crop Protection development (CPD) in India:
- Collaborate with cross-functional teams to understand business requirements and design end-to-end solutions architecture for data science applications.
- Utilize crop protection trial data, generate insights via dashboards, ML/DL/AI/LLM models that help field scientists, digital agronomists and product development heads to take informed decisions.
- Perform statistical analyses of product performance data for towards CPD and business needs.
- Work closely with Digital Agronomy team to automate field insights and query response for the field scientists, farmers, and commercial team.
- Partner with AMEA and Global Technical Excellence and Quantitative Biology team for development, testing, and implementation of new methodologies and applications in data projects.
- Use BITS and other tools and systems to provide information to CPD team in the form of data searches, queries, summaries, visualizations, analyses, and reports.
- Build deep learning/image recognition based advisory tool for the farmers via Cropwise grower App.
- Collaborate with data engineering team to seamlessly transition ML/AI innovations into scalable and reliable operational solutions.
- Prepare technical reports and presentations to communicate results and insights to both technical and non-technical stakeholders.
- Contribute to the development and testing of mobile application/enhancement on the application for various platforms like Android, iOS, or Windows.
Knowledge, Experience & Capabilities
Critical knowledge
- Master's or bachelor's degree in data science, Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative field.
- More than 4 years of experience in Python/R programming, Web Scraping, Data Wrangling, Data Visualization/R Shiny/Dash, Machine Learning, Deep Learning, AI, NLP, LLM, SQL, WS/Google Cloud/Azure
- At least 2 years of experience working in data science or related discipline in the agrochemical industry.
Critical experience
- Good understanding of agriculture, field trials, crop protection, farmer focused applications and its elements
- Strategic thinking, ability to understand customer needs, business potential in India.
- Focused on customers and dedicated to meet the expectations and requirements of internal and external customers.
- Broad understanding of digital tools, data analytics, ML, DL, AI, Data Visualization, web scraping, data summarization
- Experience in NLP, LLM, Mobile application is an added advantage.
- Strong communication skills to guide and influence stakeholders / organization to drive digital transformation.
- Collaborative, inclusive and cross functional attitude.
- Comfortable working in a matrix organization.
- Proven track-record of delivering data science solutions in agrochemical industry
Critical technical, professional, and personal capabilities
- Good people skills.
- Excellent communication skills. Highly fluent in English.
- Capability to drive and enthusiasm in product development.
- Ability to motivate and lead others.
- Ability to accept challenges and achieve results under pressure.
- Good written, oral communication and presentation skills.
- Good computer skills (including word processing, presentation preparation).
- High level of integrity and self-motivation.
Critical leadership capabilities
- Passion and enthusiasm for data science and its applications for agriculture
- Medium to extensive experience in Big-Data analysis and reporting
- Experience in operating independently in a complex matrix environment
- Focused on customers and is dedicated to meeting the expectations and requirements of customers.
People are at the heart of what we do:
- Once a year Full body check
- Competitive insurance scheme
- Employee assistance program – to take care of your and your loved ones mental health
- Paid Vacation of 30days, 12 Paid Holidays, Maternity and Paternity Leave, compassionate leaves
- Education assistance – for your career growth
- People first culture translated into 'Most Preferred place to work 2022-23 by Times group'
Note: Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity, marital or veteran status, disability, or any other legally protected status.
To learn more visit: www.syngenta.com and www.good-growth-plan
Follow us on: Twitter & LinkedIn
Syngenta Group
At the Syngenta Group, our 56,000 people across more than 90 countries strive every day to transform agriculture through tailor-made solutions for the benefit of farmers, society and our planet – making us the world's most local agricultural technology and innovation partner.
Website address - https://www.syngentagroup.com/
LI page - https://www.linkedin.com/company/syngentagroup/posts/?feedView=all
Syngenta
We are a leading, science-based agriculture company, empowering farmers to meet the demands of modern agriculture. Using cutting-edge innovation, we help farmers to grow resilient, healthy crops that can feed a growing global population, while promoting sustainable farming practices that protect and enhance our planet. Headquartered in Switzerland, we are a global agritech leader with more than 30,000 employees across over 90 countries.
https://www.syngenta.com/company
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