
Senior Data Science Leader
7 days ago
Drive forward-thinking data science initiatives that yield business impact. Lead the design of robust and scalable data platforms, leveraging expertise in AI/ML and data analysis to deliver actionable insights.
Job Responsibilities:
- Strategic Leadership: Champion data-driven decision-making by defining and implementing a company-wide data strategy aligned with business objectives.
- Architecture Design: Develop innovative data solutions using machine learning, statistical modeling, and data mining techniques to drive business growth.
- Model Development & Innovation: Leverage advanced analytics and AI/ML capabilities to create predictive models and solve complex business problems.
- Data Exploration & Analysis: Identify key trends and insights through data exploration and analysis, utilizing data visualization tools to communicate findings effectively.
- Mentorship & Team Leadership: Foster a culture of learning and growth by mentoring junior data scientists and engineers.
- Cross-functional Collaboration: Collaborate closely with product managers, engineers, and stakeholders to develop data-driven solutions.
- Research & Development: Stay up-to-date with the latest advancements in data science, exploring new methodologies and technologies.
- Data Governance & Quality: Champion data governance and quality initiatives, ensuring accuracy, consistency, and compliance.
- Thought Leadership: Represent the organization at industry conferences, publish research papers, and contribute to the data science community.
Requirements:
- Advanced degree in Computer Science, Statistics, Mathematics, or related field with focus on data science and machine learning.
- Minimum 8 years of experience in data science, with proven track record of developing successful AI/ML solutions.
- Strong expertise in statistical modeling, machine learning algorithms, and data mining techniques.
- Proficiency in programming languages like Python, R, or similar.
- Experience with big data technologies and cloud computing platforms.
- Excellent analytical skills, including hypothesis testing, regression analysis, correlation techniques, and density estimates.
- Familiarity with data visualization tools and libraries.
- Dimensionality reduction and feature extraction techniques like PCA, SVD, and LDA.
- Generative AI knowledge, particularly Transformer Models and Generative Adversarial Networks.
- Business Acumen: Strong understanding of business principles and ability to translate needs into data-driven solutions.
- Communication Skills: Excellent communication and presentation skills to explain complex technical concepts.
Competitive salary package and professional development opportunities available.
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