Data Scientist – Finance
Manchester, United Kingdom
Syngenta Group is a $28B leading science-based agtech company, operating in more than 100 countries, with more than 50’000 employees. We are proud to stand at the forefront of the tech revolution in agriculture. Using the latest digital innovations, data, and cutting-edge technologies we want to transform the way that crops are managed and enable farmers and agronomists to enhance efficiency and sustainable food production.
Our business success reflects the quality and skill of our people. We recognize that human diversity is as important to our business as biodiversity. Embracing the unique perspectives and capabilities of our employees helps us continue to catalyze innovation, maximize performance, and create business value. Join us and help shape the future of agriculture.
MAKE A DIFFERENCE
Our ambition is to provide digital technologies that enable corporate functions (Finance, HR, Legal and Procurement) to increase productivity and better serve their customers. We do this through agile partnering with each function to shape and execute their digital agenda. As vendor-neutral and Syngenta-savvy technology team, we offer ideas and opportunities and make it easy to implement fit-for-purpose solutions through the capabilities and innovation power of Syngenta Global IT & Digital.
As Data Scientist – Finance, your primary responsibility will be to build Data Science prototypes by collaborating with Finance stakeholders across Syngenta.
Your main accountabilities will be:
- You will work with our MLOPS team to deploy and automate successful prototypes in Syngenta’s Data Science platform (Amazon Sage Maker) and AWS cloud infrastructure
- Following deployment, you will monitor model performance, perform corrective actions to maintain proper accuracy and work on incremental improvements.
- You will collect data from various internal and external data sources, including Syngenta’s data lake, to deliver AI, ML and predictive analytics models fitted to the business challenges.
- Analysts, project teams and other leaders within Syngenta will work with you to translate data-driven insights into actions and decisions.
- You will form the backbone of our Data Science capabilities responsible to retain knowledge beyond project execution as well collaborate and coordinate external Data Scientists
- You will work closely with Analytics Solution Consultants, Business Analysts and Data Analysts and Engineers as well as various business stakeholders to gain the necessary information for building highly performing Data Science models.
- The goal is to support the Corporate Functions in achieving improvements by leveraging insights within Syngenta’s data.
WHAT WE ARE LOOKING FOR.
We are highly people-focused – we look for professionals who are engaged, collaborative and excellent in execution. Leaders are expected to communicate effectively, develop teams and lead by example. Our industry and our function are changing rapidly so we are looking for new team members with a strong desire to develop themselves.
You will be a great fit if you have:
- Strong track record in successfully delivering Data Science solutions in a complex business environment; 5+ years relevant experience.
- Sound experience in statistical analysis paired with data processing and statistical programming using predominantly Python in conjunction with Amazon Sage Maker and other AWS solution of the AWS stack:
- Be proficient with common libraries: NumPy, SciPy, pandas, scikit-learn, statsmodels and common algorithms like XGBoost, Random Forest, Prophet etc.
- Experience with visualization libraries: Matplotlib, Seaborn, Plotly or Power Bi, Tableau, etc.
- Good understanding of methodologies to productionize Data Science models in a CI/CD context using Sage Maker, Docker, Code Pipeline etc.
- Ability to query data from common databases (SQL) and ability to call APIs
- Proven track record of solving regression and timeseries related problem statements with various Advanced Analytics methodologies such as linear regression, machine learning, deep learning.
- Ability to perform data cleansing and work with technical and non-technical stakeholders to understand and engineer datasets/features required for modelling.
- Master’s degree in in Computer Science, Econometrics, Information Management, Information Technology, or another business or scientific field, in combination with relevant practical experience in Data Science
- Strong written and verbal communication skills in English is a must.
- Ability to work cross-functionally in a highly matrix driven organization, at times under ambiguous circumstances
- Experience in visualizing and explaining results along the various stages of a Data Science project
It will be desired if you also have:
- Further applications such as classification or clustering and optimization use cases.
- Experience with Data Science use cases within business Finance, Production and Supply or Commercial space.
WHAT WE OFFER
- A role which contributes to valuable and impactful work in a stimulating and international environment
- Flexible working arrangements and environment with an open culture and diverse workforce, a possibility of working from home
- Competitive salary and benefits package
- The opportunity to work with and learn from highly qualified and experienced employees
- A culture that promotes work/life balance, celebrates diversity and offers numerous events throughout the year
- Learning culture and a wide range of development options, including access to learning platforms (Degreed, LinkedIn Learning, O’Reilly)
- High quality office environment
Syngenta has been ranked as a top employer by Science Journal.
Learn more about our team and our mission here: https://www.youtube.com/watch?v=OVCN_51GbNI
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, marital or veteran status, disability, or any other legally protected status.
* Salary range is an estimate based on our salary survey 💰
Tags: Agile APIs AWS CI/CD Classification Clustering Computer Science Deep Learning Docker Econometrics Finance Machine Learning Matplotlib MLOps NumPy Pandas Plotly Power BI Python Scikit-learn SciPy Seaborn SQL Statistics statsmodels Tableau XGBoost
Perks/benefits: Career development Competitive pay Flex hours Team events
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