DATA SCIENTIST

Key Responsibilities:

• Collect, process, and analyze large datasets to identify trends, patterns, and actionable insights.
• Develop and implement machine learning models and algorithms to solve business problems.
• Create data visualizations and dashboards to present findings to stakeholders.
• Collaborate with cross-functional teams to understand business needs and provide data-driven solutions.
• Perform data cleaning, validation, and ensuring data integrity.
• Use statistical analysis techniques to test hypotheses and validate models.
• Stay updated with the latest data science trends, tools, and technologies.
• Document methodologies and processes used in data analysis and modeling.
• Communicate complex data insights in a clear and concise manner to both technical and non-technical audiences.

Qualifications:

• Bachelors degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. A Masters or Ph.D. degree is preferred.
• Proven experience as a Data Scientist or in a similar role.
• Proficiency in programming languages such as Python, R, or Scala.
• Experience with data analysis and visualization tools like SQL, Excel, Tableau, or Power BI.
• Strong knowledge of machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with big data technologies like Hadoop, Spark, or similar.
• Familiarity with cloud platforms like AWS, Google Cloud, or Microsoft Azure.
• Strong analytical and problem-solving skills.
• Excellent communication skills to convey complex data insights to non-technical stakeholders.
• Ability to work independently and collaboratively in a team environment.

Preferred Qualifications:

• Experience with natural language processing (NLP) and computer vision techniques.
• Knowledge of data engineering principles and experience with ETL processes.
• Certification in data science or related fields (e.g., Certified Analytics Professional (CAP), Microsoft Certified: Azure Data Scientist Associate).
• Experience with A/B testing and experimental design.

Vertical

Technology