Syngenta - Data Scientist

Responsibilities :

- Solve business problems through data exploration, descriptive analysis, statistical modelling, predictive models (including machine learning), and mathematical optimization.

- Work with Engineering teams to implement such solutions on Big Data platforms, with involvement at all stages of the development cycle from architecture to coding to testing.

- Interact with team to discuss the business problems and present solutions.

- Be capable of working independently or with Data Scientists as the situation demands.

- Have the ability to tackle a broad variety of problems in the digital domain and come up with the world class solutions and products expected in the industry.

- Develop, maintain and enhance statistical models in the business area identified

- Conceptualize modeling framework, define data requirements, create predictive variables

- Leverage state-of-the-art data mining tools and modeling techniques to solve business problems.

- Prepare documentation for developed models and provide analysis support for business strategies.

- Set up experimental designs to answer business questions

- Managing small to medium projects and experience in managing small to moderate sized teams.

- Should have statistical modeling experience in Linear Regression, Non Linear Regression, Logistic Regression, Multinomial Logit Regression, Survival Analysis, Neural Network, Forecasting Techniques, Time Series Analysis, ARIMA, Conjoint Analysis, Segmentation, Clustering Techniques, Decision Trees, Machine learning Techniques and Linear Programming etc.,

- Hands-on model building experience using SAS/R/SPSS with ability to display proficiency in data management and manipulation skills in order to perform job requirements.

- Self motivated, analytical and detail oriented.

Skills & Knowledge Technical / Functional and Managerial :

- 5 to 15 years of relevant industry/research or academics experience in Data Sciences

- years of work experience as a Data Scientist..

- Skilled in data analysis and modelling using tools such as Python, R, Julia, SAS, Scala, MATLAB, Octave, SPSS.

- Expertise in several of the following areas: Statistics, Predictive Modelling, Time Series Forecasting, Machine Learning, Linear and Mixed Integer Programming, Nonlinear Optimization, Stochastic Processes.

- Demonstrated ability, originality and creativity to work independently to solve hitherto unseen business problems as a Data Scientist.

- Passion and strong interest in learning Data Scientist skills and technologies.

- Excellent communication skills to interact with teams.

- Ability to work in a fast-paced and agile development environment.

Education :

Preferred :

- M.S. or Ph.D. in Computer Science / Mathematics / Operations Research / Physics / Economics / Engineering discipline from a top global university.

- Experience in working as a Data Scientist in Research Organisation /Universities