Sr. Data Scientist (225-821)

The Senior Data Scientist is a pivotal role in our organization, tasked with extracting insights from complex datasets and leading innovative data-driven solutions. This position demands a deep understanding of data science concepts, including machine learning, statistical analysis, and data mining, combined with a proficiency in programming and data visualization tools. The Senior Data Scientist will work closely with cross-functional teams to identify business opportunities, design experiments, and drive strategic decisions. The ideal candidate must possess excellent communication skills to convey technical information to non-technical stakeholders effectively. This is a highly skilled role that requires a blend of analytical expertise and practical experience in handling large-scale data projects.

Responsibilities

• Lead the design and development of complex data models and analytics.
• Collaborate with engineering teams to deploy machine learning models into production.
• Analyze large datasets to uncover trends, patterns, and insights for various stakeholders.
• Design and implement experiments to test hypotheses and validate modeling approaches.
• Develop predictive models to guide decision-making processes across departments.
• Work with product managers to understand business needs and translate them into data requirements.
• Communicate analytical findings to a broad audience, including executive leadership.
• Mentor and provide technical guidance to junior data scientists and analysts.
• Ensure data integrity and quality throughout the data processing lifecycle.
• Stay updated with the latest industry trends and advancements in data science.
• Identify new data sources and propose strategies for data integration and enrichment.
• Manage and prioritize multiple projects to meet deadlines and organizational goals.

Requirements

• Master's or Ph.D. in Data Science, Computer Science, or related field.
• At least 5 years of experience in data science or a related area.
• Strong proficiency in programming languages such as Python or R.
• Experience with data manipulation tools and libraries like SQL, Pandas, and NumPy.
• Advanced knowledge of machine learning techniques and statistical methods.
• Capability to work with large datasets and distributed computing tools like Hadoop.
• Excellent problem-solving skills with a keen eye for detail and accuracy.