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Responsibilities: Collect and analyze large datasets to uncover hidden patterns, trends, and insights. • Design and implement machine learning models using Python libraries like pandas, scikit-learn, numpy, Pytorch/Keras, and TensorFlow. • Evaluate the performance of machine learning models and refine them to improve accuracy andgeneralizability. • Communicate data insights to stakeholders in a clear and concise manner, using data visualization techniques and storytelling. • collaborate with data engineers, software developers, and business stakeholders to integrate data science solutions into products and services. • Stay up-to-date with the latest trends and developments in data science, machine learning, and artificial intelligence. Educational Requirements Bachelor of Engineering,Bachelor Of Science,Bachelor Of Technology,Bachelor Of Comp. Applications,Master Of Engineering,Master Of Science,Master Of Technology,Master Of Comp. Applications Additional Responsibities: • Experience with Natural Language Processing (NLP) and Computer Vision (CV) techniques. • Knowledge of DevOps methodologies and practices for continuous integration/continuous delivery (CI/CD). • Experience with data warehousing and data lakes solutions like BigQuery or Snowflake. • Familiarity with real-time data processing and streaming analytics. • Passion for learning and staying at the forefront of data science and machine learning advancements. Technical and Professional Requirements: • Master's degree in Computer Science, Statistics, Mathematics, or a related field. • 7+ years of experience in data science and machine learning with a strong focus on model development and deployment. • Expert-level knowledge of statistics, including probability theory, hypothesis testing, and statistical inference. • In-depth knowledge of machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, xgboost, and ensemble learning. • Strong programming skills in Python and proficiency in data science libraries like pandas, scikit-learn, numpy, Pytorch/Keras, and TensorFlow. • Experience with cloud computing platforms, particularly Google Cloud Platform (GCP). • Excellent data visualization skills using tools like matplotlib, seaborn, or Tableau. • Strong communication and presentation skills, both written and verbal.
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