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We are seeking a highly motivated and skilled Python Data Science Professional to join our dynamic Production Management AIOps team. This role will focus on leveraging data science techniques and Python to develop innovative solutions that optimize production processes, enhance predictive capabilities, and integrate AI/ML models into our operational workflows. The ideal candidate is a passionate data scientist with a strong understanding of Python's data science ecosystem, experience building and deploying machine learning models, and a desire to work with large datasets in a fast-paced, collaborative environment.
Job Responsibility:
Analyze large, complex datasets to identify trends, patterns, and anomalies
develop and implement machine learning models using Python libraries (e.g., scikit-learn, TensorFlow, PyTorch) to address business challenges related to production optimization, predictive maintenance, and anomaly detection
evaluate and refine model performance, ensuring accuracy and reliability
deploy and maintain machine learning models in production environments
design and implement data pipelines to collect, process, and transform data from various sources
work with both structured and unstructured data, ensuring data quality and integrity
collaborate with data engineers to integrate data science solutions into existing systems
create clear and compelling visualizations to communicate data insights to both technical and non-technical audiences
present findings and recommendations to stakeholders, effectively conveying the value of data-driven solutions
participate actively in agile development processes, collaborating with other data scientists, engineers, and product managers
stay up-to-date with the latest advancements in data science, machine learning, and AI
contribute to a positive and collaborative team environment by sharing knowledge and supporting colleagues.
Requirements:
5+ years of proven experience as a Data Scientist or similar role, with a strong focus on Python
proficiency in Python and essential data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch)
experience with statistical modeling, machine learning algorithms, and data mining techniques
strong data visualization skills using libraries like Matplotlib, Seaborn, or Plotly
experience with data engineering tools and techniques (e.g., SQL, Spark, cloud-based data warehousing solutions)
knowledge of version control systems like Git
familiarity with agile development methodologies
excellent problem-solving and analytical skills
strong communication and interpersonal skills
ability to work independently and as part of a team
ability to manage multiple tasks and prioritize effectively
passion for data science and a desire to learn and grow
bachelor's or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
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