Specialist Data Scientist
Role details
Job location
Tech stack
Job description
For the role of Sara Scientist we are looking for candidates with a broad range of skills. The responsibilities include:
- Data Science: Descriptive and predictive analytics: selection, definition, and execution of adequate algorithms, models, tests, visualizations, etc.
- Technology: Selection, definition, and execution of adequate programming frameworks, file formats, data storage solutions, automatic data flows, etc.
- Architecture: Define and/or follow best practices for Big Data & Analytics & AI use cases using on-premises solutions as well as public cloud services.
- Management: Report to project managers, clients, external and/or internal teams. Estimate resources and timelines for different tasks during the project life cycle.
- Innovation: Awareness of and continuous training in state-of-the-art techniques, models, frameworks, and tech approaches to be applied to DS & AI activities.
Requirements
We are looking for a Data Scientist to join our Vodafone Business Data & Artificial Intelligence team, to work alongside 20+ experienced, dynamic, and passionate data scientists focused on both internal and external data monetization projects. Some of our exciting projects include data engineering massive volumes of real-time, location-based data and then applying statistical analysis, making predictions on time series data, and running simulation scenarios to make recommendations, utilizing unsupervised learning to detect anomalies, developing data visualizations and dashboards for different business areas, deploying supervised learning models in production on public cloud architectures to optimize marketing campaigns, etc. If these projects spark your interest, you love technology and its applications, and you are an effective team player with excellent communication are looking forward to meeting you!, * Degree in Computer Science, Engineering, Mathematics, or related field, required
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2 years of professional experience in Data Science related positions, required
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English proficiency, required
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Master's in Data Science, AI, Data Engineering, or any data-related field, desired
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PhD and/or research experience, desired Required Technical skills:
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Experience with handling code repositories using Git.
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Expertise in at least one Cloud environment (preference on GCP, AWS) on data related services Nice to have:
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Proficiency in Python: experience handling and contributing to complex Python projects (multi-module projects, Object Oriented Programming projects - inheritance and classes, inter-dependencies between projects), building quality and production-ready code in a complex project using an IDE.
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Proficiency in Spark: understands the concept of Spark DAG, master node, executor nodes, experience on debugging a Spark execution using the Spark UIs ( debugging a memory error), knows how to appropriately size up and set up a Spark cluster (either in Dataproc - GCP, or in EMR - AWS), and to choose th manipulation and Machine Learning (, pandas, scikit-learn), with special emphasis in distributed computing frameworks (, PySpark).
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Apply appropriate ML and AI models to problems, evaluating the outcomes to maximize business impact with critical thinking.
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A strong understanding of probability theory, statistical inference, hypothesis testing, and experimental design is required for decision making with data.
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Data visualization, bringing data-driven solutions and business context together.
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Knowledge of designing and building APIs with best practices.
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Deploying and supporting Machine Learning models in live cloud environments: ML Engineering and MLOps in AWS/GCP/Azure.
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Applying Data Engineering best practices for designing, building, and maintaining data pipelines and ETL processes (, Apache Airflow).