Data Scientist
Data Scientist
Posted on :
24-05-2025
Employer Active
1 Vacancy
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Job Description
Purpose
- Be integral part of the P&S Data Science team that applies technical expertise in data management data science machine learning artificial intelligence and automation to design build deploy and maintain solutions across multiple countries.
- Work with project teams and SMEs to understand business requirements and develop appropriate data and AI/ML solutions.
- Contribute solutions with explorative predictive- or prescriptive models utilizing optimization simulation and machine learning techniques to existing and new projects.
- Work independently to build applications for data collection and processing exploration and visualization analysis regression classification and generation as required by the project and business teams.
Accountabilities
- Develop and implement complex statistical models machine learning algorithms and data mining techniques to extract insights from large datasets.
- Lead data science projects from conception to completion defining scope methodology and deliverables.
- Collaborate with business leaders to translate data insights into actionable strategies and recommendations.
- Guide and mentor junior data scientists fostering their professional development and technical skills.
- Contribute to the design and improvement of data architecture pipelines and storage solutions.
- Stay current with the latest advancements in data science and introduce new techniques or technologies to the organization.
- Establish and maintain standards for data quality documentation and ethical use of data.
- Present complex findings to both technical and non-technical audiences including executive leadership.
- Address complex business challenges using data-driven approaches and creative solutions.
- Improve the efficiency and scalability of data processing and model deployment.
- Develop deep knowledge in Syngentas P&S operations to better contextualize data insights.
- Own the design build and deploy process including collaboration with users and multi-disciplinary teams to fulfil the user business and technical requirements.
Qualifications :
Required Knowledge & Technical Skills
- Bachelors degree in Computer Science Data Science Engineering Mathematics or a related discipline (or equivalent practical experience).
- Understanding of ETL processes and data pipeline design.
- Required development skills:
- Data Science TensorFlow Scikit-learn SciPy NumPy Pandas XGBoost Keras etc.
- Programming Python with pytorch and tensorflow
- Data SQL EDA Descriptive and Predictive analysis visualization
- Preferred additional skills:
- Web services RESTful APIs and API testing JSON etc.
- Front end JavaScript Flask React Vue Django or other.
- Tools Git npm pip Heroku or other tools.
- Knowledge and hands-on experience supervised and unsupervised ML using Logistic/multi-variate regression Gradient Boosting Decision Trees Neural Network Random Forest Support Vector Machine Naive Bayes Time Series Optimization etc.
- Preference for proven experience in adapting algorithms to required models - Regression Decision Trees Random Forests LLM.
- Preference for experience in production and supply domain: production planning supply chain logistics track and trace CRM etc.
- Preference for experience in Deep Learning model development in agriculture supply chain or related domains.
- Documentation of documentation of APIs models and operational manuals (Markdown etc.).
- Must be able to work on end to end activities from design development and deployment
Required Experience
- Previous internship placement or project experience in data engineering data science software development or a related field.
- Required 2 years experience of building data science projects using AI/ML models.
- Exposure to cloud platforms such as AWS Azure Google Cloud or Data Bricks (preferred but not essential).
Additional Information :
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.
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Work :
No
Employment Type :
Full-time
Employment Type
Full-time
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