Summary

We are seeking a skilled Data Scientist to join our IT Services division, where you will play a pivotal role in transforming complex datasets into actionable business insights. This position demands a professional who can leverage advanced statistical methods and machine learning algorithms to solve critical challenges and drive strategic decision-making. The ideal candidate will bridge the gap between raw data and practical applications, ensuring that our analytical models are robust, scalable, and aligned with organizational goals.

Responsibilities

Design, develop, and deploy sophisticated machine learning models and deep learning architectures to address specific business problems.
Conduct comprehensive exploratory data analysis (EDA) to uncover hidden patterns, trends, and anomalies within large-scale datasets.
Engineer features and optimize data pipelines using Python libraries such as Pandas, NumPy, and PySpark to ensure high-quality input for modeling.
Apply natural language processing (NLP) techniques and work with Large Language Models (LLMs) and Generative AI to enhance text-based analytics and automation.
Utilize frameworks like TensorFlow, PyTorch, and Scikit-learn to build, train, and validate predictive models and neural networks.
Create interactive and intuitive dashboards using Power BI and Tableau to communicate findings effectively to stakeholders.
Perform rigorous statistical analysis and hypothesis testing to validate model performance and ensure data integrity.
Collaborate with cross-functional teams to integrate data science solutions into production environments and support ongoing model maintenance.

Requirements

Requirements:

Possess 3 to 4 years of hands-on experience in data science, analytics, or a related technical field within the IT Services sector.
Demonstrate strong proficiency in Python and SQL for data manipulation, querying, and algorithm implementation.
Show deep expertise in machine learning, statistics, and data visualization techniques.
Be well-versed in core libraries including Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, and PyTorch.
Have practical experience with NLP, Generative AI, and LLM technologies.
Display the ability to translate complex technical concepts into clear business strategies using tools like Power BI and Tableau.
Maintain a solid understanding of data analysis methodologies and the capacity to work with large, unstructured datasets.

Erforderliche Kompetenzen

Machine Learning (including deep learning architectures)Statistical Analysis and Hypothesis TestingPython programmingSQL querying and data manipulationPandas and NumPyPySpark and data pipeline engineeringTensorFlow and PyTorch (deep learning frameworks)Scikit-learn and XGBoostNatural Language Processing (NLP), LLMs and Generative AIExploratory Data Analysis (EDA)Feature engineeringData visualization using Power BI and TableauModel deployment, production integration and maintenanceWorking with large and unstructured datasets

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