Data Scientist (225-719)

A Data Scientist plays a crucial role in the data-driven decision-making processes in modern organizations. This analytical expert is responsible for collecting, analyzing, and interpreting complex data to help companies make informed decisions. The Data Scientist uses various tools and techniques, including algorithms, machine learning, and statistical analysis, to turn raw data into actionable insights. They work closely with cross-functional teams, including IT, management, and other relevant departments, to develop data-driven strategies that serve to improve company performance and deliver value to customers. The Data Scientist often communicates complex findings in a comprehensive and understandable way, which requires both a grasp of technical skills and strong communication capabilities.

Responsibilities

• Analyze large sets of structured and unstructured data to glean insights.
• Develop predictive models and algorithms to anticipate future patterns.
• Utilize statistical analysis to derive meaningful business insights from data.
• Implement machine learning techniques to enhance business performance analytics.
• Collaborate with cross-functional teams to understand business needs and challenges.
• Design and create data visualization dashboards for stakeholders’ decision-making.
• Maintain and improve data pipelines and data processing workflows for accuracy.
• Evaluate new data tools and technologies to enhance data-related processes.
• Communicate findings and recommendations to non-technical stakeholders effectively.
• Ensure data integrity and compliance with company and industry standards.
• Identify opportunities for leveraging company data to drive business solutions.
• Work with product and engineering teams to map out data requirements.

Requirements

• Bachelor’s degree in Computer Science, Statistics, Data Science, or a related field.
• Proven experience as a Data Scientist or similar data role for at least 2 years.
• Strong proficiency in programming languages like Python, R, or SQL.
• Familiarity with machine learning frameworks such as TensorFlow or scikit-learn.
• Experience with data visualization tools like Tableau, Power BI, or D3.js.
• Excellent analytical and problem-solving skills in a data-centric environment.
• Strong ability to translate complex data into understandable insights for stakeholders.
• Knowledge of statistical modelling, data mining, and data operations best practices.