Data Scientist
Summary
Build and deploy ML models using Python, TensorFlow, and PyTorch; analyze data to uncover trends and deliver dashboards and reports for stakeholders.
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What The Job Entails
Collect, clean, and preprocess data from various sources, such as databases, APIs, web scraping, or surveys Explore and analyze data to discover patterns, trends, and anomalies, and generate hypotheses and questions Build and test predictive models and machine learning algorithms, using tools such as TensorFlow, PyTorch, or Scikit-learn Evaluate and optimize the performance and accuracy of the models and algorithms, and fine-tune the parameters and features Deploy and integrate the models and algorithms into production systems and applications, using tools such as Flask, Docker, or Kubernetes Create and deliver data products and solutions, such as dashboards, reports, and visualizations, using tools such as Plotly, D3.js, or Shiny Communicate and explain complex data and findings to various stakeholders and audiences, using clear and compelling language and visuals Conduct research and experiments on new and emerging data science, machine learning, and artificial intelligence techniques and technologies, and apply them to business problems and opportunities
Job Requirements
Master's or PhD degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; or equivalent work experience Minimum of 5 years of experience in data science, machine learning, or a similar role, preferably in a tech or consulting industry Expertise in data science, machine learning, and artificial intelligence concepts, methods, and techniques, such as regression, classification, clustering, natural language processing, computer vision, or deep learning Proficient in programming languages and frameworks, such as Python, R, Java, or C++ Proficient in data analysis and manipulation tools and libraries, such as SQL, Pandas, or NumPy Proficient in machine learning and deep learning tools and libraries, such as TensorFlow, PyTorch, Scikit-learn, or Keras Proficient in data visualization and presentation tools and libraries, as Plotly, D3.js, Shiny, or Matplotlib Excellent communication, presentation, and storytelling skills, with the ability to communicate effectively with diverse stakeholders and audiences Strong analytical, problem-solving, and creative thinking skills, with the ability to use data and logic to support decisions and recommendations Ability to work in a fast-paced, dynamic, and innovative environment, and manage multiple projects and deadlines Curiosity, passion, and enthusiasm for data science, machine learning, and artificial intelligence, and their applications and implications
What The Job Entails
Collect, clean, and preprocess data from various sources, such as databases, APIs, web scraping, or surveys Explore and analyze data to discover patterns, trends, and anomalies, and generate hypotheses and questions Build and test predictive models and machine learning algorithms, using tools such as TensorFlow, PyTorch, or Scikit-learn Evaluate and optimize the performance and accuracy of the models and algorithms, and fine-tune the parameters and features Deploy and integrate the models and algorithms into production systems and applications, using tools such as Flask, Docker, or Kubernetes Create and deliver data products and solutions, such as dashboards, reports, and visualizations, using tools such as Plotly, D3.js, or Shiny Communicate and explain complex data and findings to various stakeholders and audiences, using clear and compelling language and visuals Conduct research and experiments on new and emerging data science, machine learning, and artificial intelligence techniques and technologies, and apply them to business problems and opportunities
Job Requirements
Master's or PhD degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; or equivalent work experience Minimum of 5 years of experience in data science, machine learning, or a similar role, preferably in a tech or consulting industry Expertise in data science, machine learning, and artificial intelligence concepts, methods, and techniques, such as regression, classification, clustering, natural language processing, computer vision, or deep learning Proficient in programming languages and frameworks, such as Python, R, Java, or C++ Proficient in data analysis and manipulation tools and libraries, such as SQL, Pandas, or NumPy Proficient in machine learning and deep learning tools and libraries, such as TensorFlow, PyTorch, Scikit-learn, or Keras Proficient in data visualization and presentation tools and libraries, as Plotly, D3.js, Shiny, or Matplotlib Excellent communication, presentation, and storytelling skills, with the ability to communicate effectively with diverse stakeholders and audiences Strong analytical, problem-solving, and creative thinking skills, with the ability to use data and logic to support decisions and recommendations Ability to work in a fast-paced, dynamic, and innovative environment, and manage multiple projects and deadlines Curiosity, passion, and enthusiasm for data science, machine learning, and artificial intelligence, and their applications and implications