At a Glance
- Tasks: Join our analytics team to develop AI-driven predictive models for scientific outcomes.
- Company: Global leader in analytics with a focus on innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with opportunities to collaborate across scientific disciplines.
- Why this job: Make a real impact in science using cutting-edge AI and Generative AI technologies.
- Qualifications: Experience in machine learning, Python, and data analysis; strong communication skills required.
The predicted salary is between 81000 - 99000 £ per year.
Job Description Join our global analytics team within Product Biology postgraduate education is strongly preferred.
Demonstrated experience developing machine-learning, AI or Generative AI-enabled predictive models for biological, scientific, agricultural, life-science or Crop Protection-related outcomes.
Strong knowledge of Python and relevant data science, analytics, modelling, AI and Generative AI tools and frameworks.
Practical experience with Generative AI, including Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and the evaluation of Gen AI outputs.
Strong understanding of model validation, robustness assessment and the interpretation of predictive-model performance, including the reliability, limitations and risks associated with AI and Gen AI solutions.
Ability to assess and select the most appropriate solution approach-such as predictive modelling, conventional machine learning, automation or Generative AI-based on the problem, data availability, feasibility, expected value and risk.
Knowledge of responsible AI principles, including data privacy, security, explainability, bias awareness, governance and human oversight.
Experience analysing complex datasets and translating findings into clear, actionable insights.
Experience collaborating with scientists, data scientists, software engineers or technical specialists to solve complex problems and deploy AI-enabled solutions.
Strong analytical thinking, creative problem-solving and intellectual curiosity.
Ability to work independently, manage priorities effectively and deliver work to a high standard of accuracy.
Strong communication skills, including data visualisation and storytelling for specialist and non-specialist audiences.
Professional proficiency in English.
Preferred Academic or professional experience in biology, chemistry, ecology, environmental science, biokinetics or related scientific domains.
Experience working with laboratory, field-trial, environmental or other complex scientific datasets.
Experience with interdisciplinary or multiscale modelling approaches.
Experience building, evaluating or deploying AI/Gen AI applications in scientific, R
Senior Data Scientist - Ai And Genai employer: Syngenta Crop Protection
Syngenta Crop Protection is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the field of genetic toxicology. Located at Jealott's Hill, UK, employees benefit from extensive perks such as up to 31.5 days of holiday, a competitive bonus scheme, and a robust pension plan, all while contributing to sustainable agricultural solutions. With a strong commitment to diversity and employee growth, Syngenta provides meaningful opportunities for professional development in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - Ai And Genai
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Syngenta Crop Protection!
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We think you need these skills to ace Senior Data Scientist - Ai And Genai
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Syngenta Crop Protection, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Syngenta Crop Protection. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Syngenta Crop Protection
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Syngenta Crop Protection!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
