Key Responsibilities:

• Collect, clean, and preprocess data from various sources for analysis.
• Analyze large datasets to uncover patterns, trends, and insights.
• Build predictive models and machine learning algorithms to address business challenges.
• Develop and implement data-driven solutions to improve decision-making processes.
• Visualize data and present findings to both technical and non-technical stakeholders.
• Assist in designing and conducting experiments to optimize business processes.
• Work closely with cross-functional teams to identify key metrics and KPIs.
• Communicate insights effectively through reports, dashboards, and presentations.
• Stay updated on the latest trends in data science, machine learning, and artificial intelligence.

Required Qualifications:

• Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
• Strong understanding of statistical analysis and data modeling techniques.
• Proficiency in programming languages such as Python or R for data manipulation and analysis.
• Familiarity with machine learning libraries like scikit-learn, TensorFlow, or Keras.
• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib.
• Knowledge of SQL and experience with database management.
• Ability to work with large datasets and understand data cleaning techniques.
• Strong problem-solving skills and attention to detail.
• Good communication skills and ability to present technical information to non-technical audiences.
• Ability to work well in a team-oriented, collaborative environment.

Preferred Skills:

• Internship or academic project experience related to data science or analytics.
• Familiarity with big data technologies (Hadoop, Spark) is a plus.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure is a bonus.
• Knowledge of deep learning techniques and frameworks.
• Familiarity with data wrangling and ETL processes.

Salary and Benefits:

• Competitive salary based on experience and qualifications.
• Health and wellness benefits, including medical and dental coverage.
• Paid vacation days and public holidays.
• Opportunities for professional development and training.
• A collaborative and dynamic work environment with mentorship opportunities.