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Data Science Engineernew Job Opening In Kiel – Now Hiring beON consult

Data Science Engineernew

    Germany Jobs Expertini Expertini › Germany › Jobs › Kiel › Mathematical Science Occupations › Data Science Engineernew

Job description

Responsibilities

A Data Science Engineer typically plays a crucial role in bridging the gap between data science and engineering.

Their responsibilities revolve around leveraging data science techniques and technologies to build scalable, efficient, and reliable data-driven solutions role

  • Collaborate with data scientists, software engineers, and stakeholders to understand data requirements and business objectives

  • Design, develop, and maintain scalable data pipelines for ingesting, processing, and analyzing large volumes of data

  • Implement data preprocessing, feature engineering, and data transformation techniques to prepare data for analysis and modeling

  • Build and deploy machine learning models into production environments, ensuring scalability, efficiency, and reliability

  • Develop software applications, libraries, and APIs for automating data processing, analysis, and visualization tasks

  • Implement machine learning algorithms using programming languages such as Python and R to develop predictive models and data-driven solutions

  • Conduct text analysis, including processing unstructured data and implementing Natural Language Processing (NLP) techniques and Integrate Large Language Models (LLM) into projects

  • Perform pattern analysis to identify trends and anomalies within datasets and predict future values using predictive modeling techniques

  • Conduct Data Science analyses to extract insights and identify relationships within data through exploratory data analysis (EDA)

  • Prepare data for analysis by cleaning, transforming, and engineering features to enhance the performance of machine learning models and improve predictive accuracy

  • Demonstrate proficiency in technologies and concepts related to data science, including NLP, neural networks (NN), computer vision (CV), exploratory data analysis (EDA), supervised and unsupervised machine learning, and predictive modeling

  • Implement general MLOps practices such as Continuous Integration (CI) and Continuous Deployment (CD) on local Kubernetes clusters, GPU servers, or cloud platforms like Azure AKS and Azure MLOps/Databricks

  • Implement MLOps practices, including Continuous Integration (CI) and Continuous Deployment (CD), to streamline the deployment and management of machine learning models in production environments.

  • Ensure code quality through intensive code reviews and support and mentor junior developers and students

  • Engage in both technical and non-technical communication with stakeholders

  • Manage day-to-day MLOps tasks in the Data Science and Machine Learning domain

  • Contribute to the conceptualization of future applications, domains, and roadmaps for Artificial Intelligence initiatives

    • Qualifications

  • Bachelor’s degree or Masters in Computer Science, Data Science, Engineering or a related field

  • At least 3 years of experience in Data Science, Machine Learning or Software Engineering roles

  • Proficiency in programming languages such as Python, R, Java, or Scala

  • Experience with data processing frameworks such as Hadoop, Spark, or Flink

  • Proficiency in natural language processing (NLP) techniques and tools (e.g., NLTK, spaCy, BERT).

  • Familiarity with large language models (LLM) such as GPT-3, BERT, or XLNet

  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Hadoop, Spark) is a plus

  • Experience in machine learning algorithms, techniques, and libraries such as scikit-learn, TensorFlow, PyTorch or Keras

  • Familiarity with data visualization tools such as Matplotlib, Seaborn, Tableau

  • Experience with MLOps practices, including model deployment and monitoring, is a plus

  • Knowledge of SQL for data querying and manipulation

  • Understanding of version control systems like Git for collaboration and code management.Understanding of containerization and orchestration tools like Docker and Kubernetes

  • Excellent analytical, problem-solving, and communication skills

    • Contact Us


    If we have gained your interest, we look forward to receiving your application with an up-to-date CV.

    We know that you are very busy and therefore do not expect a cover letter.

    Please use the job title “Data Science Engineer” in the subject line of your application.

    Required Skill Profession

    Mathematical Science Occupations


    • Job Details

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    Unlock Your Data Science Potential: Insight & Career Growth Guide


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    The Work Culture

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    2. Loyalty

    3. Impartiapty

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    5. Accountabipty

    6. Respect for human rights

    7. Obeying Germany laws and regulations

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