Data Scientist - Intern

Job Summary:

We are seeking a talented and motivated Junior Data Scientist to join our data analytics team. As a Junior Data Scientist, you will work on various data projects, assisting in data analysis, modeling, and developing machine learning solutions. You will collaborate with senior data scientists and cross-functional teams to extract insights from data and contribute to data-driven decision-making. The ideal candidate should have a strong foundation in data science concepts, programming skills, and a passion for solving complex problems using data.

Qualifications:

· Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. (Graduated in 2024 or before)

· Strong understanding of data science concepts, statistical analysis, and machine learning algorithms with ( 1 to 2 Years) experience

· Proficiency in programming languages such as Python ( 1 to 2 Years) or R ( 1 to 2 Years) for data manipulation, analysis, and modeling.

· Familiarity with data visualization tools and libraries, such as Matplotlib or Tableau.

· Experience with data preprocessing, feature engineering, and data cleaning techniques.

· Basic knowledge of SQL for data querying and manipulation.

· Strong problem-solving skills and ability to think analytically.

· Excellent communication skills, with the ability to effectively present complex concepts and findings to non-technical stakeholders.

· Ability to work collaboratively in a team environment and contribute to team goals.

· Knowledge of cloud platforms like AWS or Azure and experience working with big data technologies are desirable.

· Familiarity with version control systems like Git and knowledge of software development practices is a plus

· Basic Understanding of Machine Learning Operations (MLOps): Familiarity with the lifecycle of machine learning models from development to deployment and maintenance.

· Knowledge of Data Ethics and Privacy: Understanding of data privacy laws (like GDPR) and ethical considerations in data science.

· Adaptability to New Technologies: Ability to quickly learn and adapt to new data analysis tools and techniques as they emerge.

· Critical Thinking: Ability to approach problems critically and propose innovative solutions.

· Project Management Skills: Basic project management skills to manage tasks efficiently and meet deadlines.

Responsibilities:

· Assist in data collection, preprocessing, and cleaning to ensure data quality and usability for analysis.

· Perform exploratory data analysis to identify patterns, trends, and relationships in the data.

· Develop and implement statistical and machine learning models to solve business problems.

· Collaborate with senior data scientists to design and execute experiments, analyze results, and generate actionable insights.

· Conduct data visualization to effectively communicate findings and present insights to stakeholders.

· Assist in developing and maintaining data pipelines and workflows for data ingestion, transformation, and analysis.

· Stay abreast of the latest data science techniques, tools, and methodologies, and apply them to enhance analytics capabilities.

· Collaborate with data engineering and IT teams to ensure seamless integration and data availability for analysis.

· Contribute to developing and improving data science workflows and best practices.

· Document and communicate the methodology, assumptions, and limitations of data models and analyses.

· Assist in Model Deployment: Aid in deploying machine learning models into production environments, ensuring they run efficiently and reliably.

· Participate in Code Reviews: Engage in code review processes to ensure quality and adherence to best practices.

· Data Quality Assurance: Regularly check data sources for integrity and accuracy.

· Continuous Learning: Commitment to continuous learning and staying updated with advancements in data science and related fields.