Data Scientist (225-1013)

A Data Scientist is a pivotal role in the modern, data-driven world of business. Tasked with cultivating actionable insights from vast amounts of data, a Data Scientist employs a variety of analytical skills and practices to delve deeply into datasets, extracting valuable information that guides complex decision-making processes. This role requires a unique blend of statistical knowledge, programming abilities, and business acumen to develop predictive models, identify trends, and drive strategic initiatives. The ideal candidate will be adept in using cutting-edge technologies and software to analyze structured and unstructured data sources, applying sophisticated algorithms and machine learning techniques to uncover hidden patterns and relationships within the data. The aim is to inform and enhance business strategies, ensuring that companies remain competitive and innovative in their approaches.

Responsibilities

• Analyze large datasets to extract valuable insights that inform decision-making.
• Develop predictive models and machine learning algorithms suited to business goals.
• Collaborate with cross-functional teams to integrate data-driven solutions effectively.
• Design and implement data processing and cleaning techniques for structured data.
• Identify data sources and establish robust data collection systems and pipelines.
• Present findings and trends through compelling data visualizations and reports.
• Stay updated with the latest technological advancements in data science and analytics.
• Conduct hypothesis testing and statistical analyses to validate findings and models.
• Contribute to strategic planning and decision-making with evidence-based insights.
• Ensure data accuracy, quality, and integrity through meticulous data validation.
• Implement retrieval systems for efficient access and analysis of large data sets.
• Mentor junior data scientists, providing guidance and sharing best practices.

Requirements

• Bachelor’s degree in Data Science, Statistics, Computer Science, or related field.
• Proficiency in programming languages such as Python, R, and SQL is essential.
• Experience with data visualization tools like Tableau, Power BI, or similar.
• Strong understanding of machine learning algorithms and statistical modeling.
• Excellent communication skills to convey complex data insights effectively.
• Experience with big data technologies such as Hadoop, Spark, or similar platforms.
• Ability to manage multiple projects and deliver results under tight deadlines.