A.I. Engineer

What this role is about?

We are seeking a skilled AI Developer to join our AI applied team and lead the development of innovative artificial intelligence solutions across multiple business functions with a special focus on Global Supply Chain, Finance and R&D. Your expertise in applied machine learning and data analysis will be critical in creating intelligent and transformative AI applications. You will work closely with cross-functional teams to conceptualize, design, test, and deploy AI projects that drive innovation and provide value in the rapidly evolving field of artificial intelligence. Join us and be a part of shaping the future of AI.

The role needs a combination of business focus, strong analytical/statistical and problem-solving skills. Candidate understands statistical, econometric and machine learning methods to classify, cluster, segment and predict complex questions. With a deep understanding of the business levers, she/he will collaborate with other business functions, data analysts, data engineers and data strategists to specify and drive data opportunities, as well as work with other AI providers to develop the necessary A.I. capabilities, provide actionable insights and recommendations.

What will you do?

Work with other business functions, data analysts, and data strategists to identify and propose advanced analytical opportunities with a special focus on customer and consumer experience
Identify what data is available and relevant, including internal and external data sources, leveraging new data collection processes

Collaborates with other business functions and markets to select the relevant sources of information Partners with external providers of data and data science A.I. to developed tailored solutions for

enrich, segment, and profile data
predict forecast for better planning
classify data for process efficiency
improve machine predictive maintenance and parameter tuning
enhance consumer and customer experience
improve the employee experience

Define the validity of the information, how long the information is meaningful, and what other information it is related to.
Define data quality standards in the context of the specific initiatives.
Identify and qualify where information can be stored or what information, external to the organization may be used in support of the data initiative
Identify in collaboration with data analysts the main features and business drivers needed to optimize the model
In collaboration with data analysts and data strategists, identifies and collects data from all kinds of different sources such as web APIs, internal database, external customer databases, and so on.
This will involve extending JTI’s data with second and third party sources of information when needed
Use algorithms to efficiently go through large datasets and apply treatments, filters and conditions to internal and external data.
Process cleanses, and verifies the integrity of data used for analysis
Present and depict the rationale of the findings in easy to understand terms for nonscientific audience
Provide on-going tracking and monitoring of performance of decision systems and statistical models

What are we looking for?

University Degree in Data Science, Economics, Statistics, Applied Math, Physics, Operations Research, Engineering or a related field. PhD is a plus
5+ years of computer science development professional experience (with relevant industry experience) focusing on artificial intelligence and analysis across multinational organizations
Should be passionate about challenging prediction problems, finding insights in data, and applying your conclusions to drive clear and practical business impact
Excellent written and communication skills to report back the findings in a clear, structured manner are required
Proactive mindset for identifying business problems on their own and proposing, strategizing and implementing data-based solutions delivering added value
Strong interpersonal skills and ability to identify and collaborate with key stakeholders across functions
Experience working with data science languages such as R or Python and SQL
Knowledge of major Data Science platforms (i.e. Microsoft Azure ecosystem)
Knowledge of major Big data storage (i.e. data lake), analytical engines (i.e.Spark), and API management for model consumption
Mastering common supervised and unsupervised Machine Learning techniques, as well as forecasting techniques
Knowledge of Deep Learning methods and Generative AI techniques
Proficiency on working with structured and unstructured (i.e., textual or visual) data sources

What Are The Next Steps – Recruitment Process

Thank you very much for your interest in the role. We will make sure every candidate will receive a reply within 2 weeks after the application deadline.

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