Data Science Engineer

20 hours ago

tamil nadu, India Populus Empowerment Network Full time

Key Responsibilities:Develop and maintain backend systems for data processing and analyticsImplement and optimize machine learning models for OCR and NLP applicationsLeverage Python and related frameworks to process large datasets efficientlyWork with data engineering teams to integrate data pipelines and data sources into backend systemsDesign, implement, and deploy robust, scalable, and secure backend servicesApply Data Science concepts to analyze, interpret, and leverage data for actionable insightsCollaborate with front-end developers to integrate user-facing elements with server-side logicStay up-to-date with the latest trends in data science, machine learning, OCR, and NLP technologiesTroubleshoot and resolve issues in data models, pipelines, and production systemsMentor and guide junior developers and contribute to team knowledge sharingRequired Skills and Qualifications:4+years of experience as a Data Scientist or Backend DeveloperProficiency in Python and relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch)Strong knowledge of Data Science concepts, statistical analysis, and machine learning algorithmsExperience with Optical Character Recognition (OCR) techniques and tools (e.g., Tesseract, OpenCV)Strong understanding and experience in Natural Language Processing (NLP) concepts (e.g., Named Entity Recognition, Sentiment Analysis, Text Classification)Experience with backend frameworks and technologies (e.g., Django, Flask, FastAPI)Familiarity with database systems (SQL, NoSQL) and cloud platforms (AWS, Azure, GCP)Solid experience with version control (e.g., Git) and agile development processesExcellent problem-solving and analytical skillsStrong communication skills and the ability to work effectively in a collaborative team environmentPreferred Qualifications: Immediate Joiners are preferred.Master’s degree or higher in Computer Science, Data Science, or a related fieldExperience with deploying machine learning models in productionFamiliarity with containerization technologies (e.g., Docker, Kubernetes)Experience with big data tools and technologies (e.g., Hadoop, Spark)

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