Data Scientist (225-618)

A Data Scientist plays a critical role in leveraging data to drive organizational decisions, innovation, and strategy. With our increasingly data-centric world, data scientists are core to harnessing the potential locked within vast amounts of data. These professionals use a blend of technical skills, analytical proficiency, and business acumen to transform raw data into valuable insights. This position requires someone adept at statistical analysis, possess a strong understanding of machine learning algorithms, and is skilled in using data visualization tools to present complex data insights in an understandable manner. Data Scientists work collaboratively with stakeholders across various departments to identify opportunities for leveraging company data to drive business solutions. They are expected to maintain a balance between analytics, programming, and business needs, ensuring data-driven solutions align with the strategic goals of the organization.

Responsibilities

• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Perform exploratory data analysis (EDA) to discover trends and patterns.
• Assess the effectiveness and accuracy of data sources and data gathering techniques.
• Advise organizational leaders on data-driven decision-making strategies.
• Create and maintain interactive dashboards and visualizations for data presentation.
• Optimize joint development efforts through tools like GitHub, JIRA, etc.
• Identify valuable data sources and automate collection processes.
• Collaborate with engineering teams to integrate data-driven solutions into products.
• Develop processes and tools to monitor and analyze model performance and data accuracy.
• Stay current with emerging data technologies and industry trends.

Requirements

• Bachelor's or Master's degree in Computer Science, Statistics, or related field.
• Proven experience in data mining and data analysis techniques.
• Strong knowledge of statistical programming languages like R and Python.
• Experience with big data tools such as Hadoop, Spark is advantageous.
• Familiarity with database management systems such as SQL, NoSQL databases.
• Exceptional problem-solving skills and ability to work under tight deadlines.
• Ability to explain complex data insights to non-technical stakeholders.