Data Scientist | 3+ Years of Experience - San Francisco

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

Responsibilities:

• • 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 the business problems and opportunities