About the role

As a Junior Data Scientist, you will work closely with senior data scientists and other cross-functional teams to analyze, interpret, and visualize data, contributing to the development of data-driven solutions while also delivering training sessions to build data literacy across the organization.

Key Responsibilities

Your key responsibilities shall include, but not be limited to, the following:

Training Delivery:

• Conduct engaging and informative physical and virtual training sessions for individuals or groups.
• Adapt training methods to accommodate various learning styles and levels of proficiency.
• Provide real-world examples and case studies to enhance practical application.
• Collaborate with senior data scientists and stakeholders to understand business objectives and formulate data-driven solutions.
• Clean, preprocess, and analyze large datasets to extract meaningful insights.
• Apply statistical techniques and machine learning algorithms to solve business problems and improve decision-making processes.
• Assist in the development and implementation of predictive models and algorithms.
• Create data visualizations and reports to effectively communicate findings to both technical and non-technical audiences.
• Stay updated on industry trends and emerging technologies in data science.
• Collaborate with cross-functional teams to integrate data science solutions into existing systems and processes.
• Perform any other duties as shall be assigned by the company from time to time.

Qualifications

• Bachelor's degree in Data Science, Statistics, or a related field.
• Strong understanding of fundamental statistical concepts and machine learning algorithms.
• Proficient in programming languages, such as Python, Excel, Tableau, Power BI.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Solid understanding of database management and SQL.
• Excellent problem-solving and critical-thinking skills.
• Strong communication skills to convey complex findings to both technical and non-technical stakeholders.
• Ability to work collaboratively in a team environment.
• Eagerness to learn and adapt to new technologies and methodologies.

Preferred Qualifications

• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of cloud platforms (e.g., AWS, Azure, GCP).
• Familiarity with version control systems (e.g., Git).
• Previous internship or project experience in a data-related role.
• Previous training experience in a data related role.

• Conduct engaging and informative physical and virtual training sessions for individuals or groups.
• Adapt training methods to accommodate various learning styles and levels of proficiency.
• Provide real-world examples and case studies to enhance practical application.
• Collaborate with senior data scientists and stakeholders to understand business objectives and formulate data-driven solutions.
• Clean, preprocess, and analyze large datasets to extract meaningful insights.
• Apply statistical techniques and machine learning algorithms to solve business problems and improve decision-making processes.
• Assist in the development and implementation of predictive models and algorithms.
• Create data visualizations and reports to effectively communicate findings to both technical and non-technical audiences.
• Stay updated on industry trends and emerging technologies in data science.
• Collaborate with cross-functional teams to integrate data science solutions into existing systems and processes.
• Perform any other duties as shall be assigned by the company from time to time.

• Python
• Excel
• Tableau
• Power BI
• Pandas
• NumPy
• scikit-learn
• TensorFlow
• PyTorch
• SQL
• Problem-solving
• Critical-thinking
• Communication
• Teamwork
• Adaptability

• Bachelor's degree in Data Science, Statistics, or a related field.
• Strong understanding of fundamental statistical concepts and machine learning algorithms.
• Proficient in programming languages, such as Python, Excel, Tableau, Power BI.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Solid understanding of database management and SQL.
• Excellent problem-solving and critical-thinking skills.
• Strong communication skills to convey complex findings to both technical and non-technical stakeholders.
• Ability to work collaboratively in a team environment.
• Eagerness to learn and adapt to new technologies and methodologies.
• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of cloud platforms (e.g., AWS, Azure, GCP).
• Familiarity with version control systems (e.g., Git).
• Previous internship or project experience in a data-related role.
• Previous training experience in a data related role.