SUMMER INTERNSHIP - AUTOMATED TICKET PRE-CHECK SYSTEM

Descripción del puesto.
Your tasks This summer internship aims to establish a foundation to develop an advanced automated system for pre-checking BMC support tickets within the IT operations of our organization, leveraging machine learning (ML) techniques.
By employing ML algorithms for natural language processing (NLP), predictive analytics, anomaly detection, and recommendation systems, the system will intelligently analyze ticket requirements such as permissions, location, acceptable resource ranges, and support team assignments.
Through ML-driven automation, the system will standardize ticket handling processes, prioritize tickets for processing, identify errors or anomalies, and provide recommendations for resolution.
This internship offers students a unique opportunity to gain practical experience in developing ML-powered solutions for optimizing IT operations and enhancing customer satisfaction.
What you will do.
* Data Collection and Preprocessing.
* Gather historical support ticket data, including ticket descriptions, attributes, and outcomes.
* Preprocess the data to clean and format it for ML model training.
* Feature Engineering.
* Identify relevant features from the ticket data, such as text content, permissions, locations, and resource requirements.
* Engineer additional features, if necessary, to enhance the performance of ML models.
* Model Selection and Training.
* Explore and evaluate various ML algorithms suitable for different aspects of ticket pre-checking, predictive analytics, and anomaly detection.
* Train ML models using the preprocessed ticket data, optimizing hyperparameters and model architectures as needed.
* Documentation and Reporting.
* Document the system architecture, ML algorithms, and implementation details for future reference.
Read more Read less Your profile * Programming Proficiency.
Proficiency in programming languages such as Python is required for implementing machine learning algorithms and developing software components; * Understanding of Machine Learning.
Basic understanding of machine learning concepts and algorithms, including data preprocessing, model selection, and evaluation; * Analytical Skills.
Strong analytical skills to analyze data, identify patterns, and derive insights; * Problem-Solving Abilities.
Ability to tackle complex problems and develop innovative solutions using machine learning techniques; * Teamwork and Collaboration.
Capacity to work effectively in a team environment, collaborate with colleagues, and communicate ideas clearly; * Time Management.
Good time management skills to adhere to deadlines, prioritize tasks, and allocate time effectively; * Documentation Skills.
Ability to document the development process, system architecture, and implementation details comprehensively; * Learning Orientation.
Eagerness to learn new technologies and methodologies related to machine learning and artificial intelligence * Professionalism.
Professional demeanor and commitment to maintaining confidentiality, integrity, and professionalism while working on sensitive organizational data and projects; * Adaptability.
Willingness to adapt to evolving requirements, learn new tools and techniques, and contribute to continuous improvement throughout the internship.
Read more Read less Our offer What we offer.
* Exciting and diversified projects * Wide network to research and development parties * Modern leadership culture * Individual choice of working times * Promotion of personal development If you meet the requirements, you will be contacted within 15 days.
Ready to drive with Continental? Take the first step and fill in the online application.
Read more Read less About us Continental develops pioneering technologies and services for sustainable and connected mobility of people and their goods.
Founded in , the technology company offers safe, efficient, intelligent and affordable solutions for vehicles, machines, traffic and transportation.
In , Continental generated sales of EUR41.
billion and currently employs around people in 56 countries and markets.
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