Data Scientist (225-905)

A Data Scientist is a pivotal role in any organization looking to leverage data for strategic decision-making. The primary responsibility of a Data Scientist is to extract insights and valuable information from large volumes of data, which can help companies innovate and gain a competitive edge. This involves cleaning, organizing, and analyzing data, as well as developing and implementing advanced analytics models. With their expertise in statistical analysis, algorithms, and machine learning, Data Scientists transform structured and unstructured data into actionable insights. They are integral to optimizing performance, understanding customer behavior, enhancing product development, and fostering business growth. A thorough grounding in mathematics, statistics, and computer science, combined with excellent problem-solving skills and domain knowledge, is critical for success in this role.

Responsibilities

• Analyze large datasets to extract actionable insights that inform business strategies.
• Design, develop, and implement predictive models using machine learning techniques.
• Collaborate with cross-functional teams to understand and meet data-driven demands.
• Communicate complex data findings clearly to non-technical stakeholders and leadership.
• Create data visualizations that help interpret and communicate data trends effectively.
• Develop and maintain scalable databases and data pipelines for data access and analysis.
• Conduct thorough data cleansing processes to ensure data accuracy and reliability.
• Stay updated with the latest innovations and best practices in data science and analytics.
• Assess the effectiveness and accuracy of data sources and data-gathering techniques.
• Monitor and report on data quality and escalate issues as necessary to the IT department.
• Support the development of data-driven products and tools to enhance business processes.
• Identify emerging trends and patterns in complex datasets to drive competitive advantage.

Requirements

• Bachelor's or Master’s degree in Data Science, Computer Science, or related field.
• Proven experience in data analysis, statistical modeling, and machine learning techniques.
• Proficiency in programming languages such as Python, R, or Java is essential.
• Strong knowledge of data visualization tools, such as Tableau, Power BI, or Matplotlib.
• Experience with big data platforms such as Hadoop, Spark, or similar technologies.
• Excellent problem-solving capabilities and sharp analytical skills are required.
• Ability to translate complex datasets into actionable business strategies and insights.