Senior Data Scientist

Posted 2024-09-23

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💎 Seniority level: Senior, 5+ years

📍 Location: United States

💸 Salary: 96600 - 135000 USD per year

🔍 Industry: Vehicle security technology

🏢 Company: Canopy

🗣️ Languages: English

⏳ Experience: 5+ years

🪄 Skills: PythonSQLCloud ComputingMachine LearningPyTorchTableauAlgorithmsAzureData engineeringData scienceGrafanaTensorflowCommunication SkillsProblem Solving

Requirements:

Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
5+ years of experience in data science, with a strong background in statistical analysis, machine learning, and predictive modeling.
Authorized to work in the United States.
Proficiency in programming languages such as Python or R.
Strong expertise in SQL and experience working with large-scale databases and data processing frameworks.
Demonstrated ability to work with complex data sets, including data cleaning, transformation, and feature engineering.
Experience with data visualization tools such as Tableau, Grafana, or Matplotlib.
Strong problem-solving skills, with the ability to work independently and manage multiple projects simultaneously.
Excellent communication skills, both written and verbal, with the ability to convey complex technical concepts to non-technical stakeholders.

Responsibilities:

Lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex business problems.
Collaborate with cross-functional teams, including product managers, engineers, and business stakeholders, to identify data-driven opportunities and translate them into actionable insights.
Analyze large datasets to extract meaningful patterns, trends, and relationships, leveraging statistical methods, machine learning techniques, and data visualization tools.
Develop and validate approaches, ensuring accuracy, robustness, and scalability for deployment in production environments.
Communicate findings and recommendations to both technical and non-technical audiences through detailed reports, presentations, and data visualizations.
Mentor and provide guidance to junior data scientists and analysts, fostering a culture of continuous learning and innovation.

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