Scientist
- Hiring from
- Tunisia
- Work type
- Hybrid
- Posted
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Infor Decision Analytics and Science (IDeAS) is a division of Infor that provides AI/ML solutions for various industries. We use advanced predictive and prescriptive analytics to create value-driven solutions. Our goal is to enable fast and effective decision automation for all business functions.
The Data Science Engineers in IDEAS are the brain behind every data-driven solution. This role relies on a combination of analytics and technical expertise to turn the data vision into reality. As a Data Science Engineer, you are responsible for designing, building, and operationalizing large-scale predictive and prescriptive analytics to solve business problems that are important to Infor customers.
A Typical Day in the Life Includes:
A Day in The Life Typically Includes:
- Design, build and set up end to end lifecycle of machine learning solutions, including ML model orchestration and data pipelines.
- Design and Build ETL/ELT pipelines from customer data sources to support ML solutions requirements.
- Lead discussions with business stakeholders to identify business challenges that can be solved with AI/ML.
- Communicate the results and their implications to the business stakeholders.
- Perform and review exploratory data analysis on large and complex datasets to assess data quality, extract, and share insights.
- Design and build innovative and pragmatic solutions using the latest AI/ML technologies in different industries.
- Review work of junior team members within a project.
Basic Qualifications:
What You Will Need:
- Engineering degree (or foreign equivalent) in Mathematical Modeling, Operations Research, Computer Science, Telecommunications, Electrical, Industrial or a related quantitative discipline from an accredited university.
- Deep real-world experience in designing and implementing full machine learning and/or optimization solution pipelines, from ETL to data pre-processing, to quantitative data analysis, to model prototyping, to model deployment and inference.
- Proficient programming skills in Python and data-querying skills in SQL and/or PySpark, etc.
- Ability to communicate your ideas/code clearly through blog posts, kernels, GitHub.
- Effective verbal and written communication, and presentation skills to explain difficult technical topics to different audiences from scientists to engineers to business partners.
- Good data modeling and problem-solving skills.
- A strong collaborative mindset with great interpersonal skills to help solve complex business problems.
- Hands on experience in analytics tools: Tableau, Power BI…
Preferred Qualifications:
What Will Put You Ahead?
- Knowledge of machine learning algorithms with frameworks such as TensorFlow, PyTorch, or Keras.
- Experience in building Timeseries forecasting and recommendation models.
- Experience in Demand Forecasting, Anomaly Detection, Pricing or Recommendation solutions.
