Sr Data Scientist Lead - Deep Learning

Position: Sr Data Scientist Lead - Deep Learning

Duration: Full time position/ Long term contract

Location: Santa Clara, CA (Onsite Position)

Interview process: Teams

Job Requirements

• A minimum of 7 years of experience in data science, with a proven track record of delivering impactful data-driven solutions.
• In-depth expertise in statistical analysis, machine learning algorithms, and predictive modeling techniques.
• Strong programming skills in languages such as Python, etc., with experience in data manipulation, cleaning, and analysis.
• Experience in leading and managing a team of data scientists, including setting goals, providing guidance and feedback, and ensuring project success.
• Proven ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders.
• Strong problem-solving skills and the ability to think strategically to identify opportunities for leveraging data and analytics to drive business outcomes.
• Familiarity with cloud platforms, such as DataBricks or Cloudera, and experience in deploying and managing data science models in a cloud environment.
• Strong project management skills, with the ability to prioritize and manage multiple projects simultaneously.

Qualifications

• Master's or Ph.D. degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Proven experience in leading and managing a team of data scientists, including hiring, training, and mentoring.
• Strong domain knowledge in a specific industry or sector, such as semiconductor or material science.
• Publications or research experience in the field of data science, machine learning, or related areas.
• Experience in working with unstructured data, such as text or image data, and applying natural language processing or computer vision techniques.
• Knowledge of advanced analytics techniques, such as deep learning or reinforcement learning.
• Experience in working with data engineering teams to build and optimize data pipelines for data processing and analysis.
• Familiarity with data privacy and security regulations, and ensuring compliance in data science projects.
• Strong business acumen and the ability to understand and align data science initiatives with business goals and objectives.
• Active participation in data science communities, conferences, or meetups, and a passion for staying up-to-date with the latest advancements in the field.

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