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Head of Data Science

Posted 6 days agoViewed

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💎 Seniority level: Director, 8+ years

📍 Location: Brazil, Argentina, Ukraine, Romania, Mexico

🔍 Industry: Insider Risk Management

🏢 Company: Teramind👥 51-100Productivity ToolsSecurityCyber SecurityEnterprise SoftwareSoftware

🗣️ Languages: English

⏳ Experience: 8+ years

🪄 Skills: AWSLeadershipPythonSQLData AnalysisMachine LearningMLFlowAlgorithmsData engineeringData scienceREST APIData visualizationTeam managementData modeling

Requirements:
  • 8+ years of experience in data science, machine learning, or a related field, with at least 3 years in a leadership role.
  • Strong expertise in machine learning algorithms and statistical modeling techniques.
  • Hands-on experience with data science tools and frameworks, including Python, familiarity with ML frameworks
  • Expertise in anomaly detection, time series analysis, and behavioral modeling
  • Experience applying machine learning to security challenges preferred
  • Proven track record in deploying data-driven solutions that have contributed to business growth.
  • Excellent communication skills for effectively presenting complex technical concepts to non-technical stakeholders.
  • Strong analytical and problem-solving skills, complemented by a strategic mindset.
  • Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field.
Responsibilities:
  • Lead and manage a high-performing data science team in developing behavioral analytics models, fostering a culture of innovation and continuous improvement.
  • Define and execute the data science strategy in alignment with business objectives, ensuring robust analytical methodologies.
  • Oversee the design and implementation of machine learning models and frameworks to solve pertinent business challenges.
  • Establish methodologies for baselining normal user behavior
  • Develop risk scoring mechanisms for potential security threats
  • Collaborate with security experts to translate threat patterns into detection models
  • Monitor and assess industry trends and advancements in data science and machine learning, leveraging new technologies and methodologies.
  • Guide the team in conducting exploratory data analysis, performance tuning of algorithms, and ensuring the accuracy of predictions.
  • Establish key performance indicators and metrics to evaluate the effectiveness of data science initiatives.
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