Job Description:
As a Junior Data Scientist at HSG Co., you will play an essential role in data analysis, modeling, and developing machine learning solutions. You will work closely with the data science and product design team to extract meaningful insights from data, create predictive models, and drive data-driven decision-making within the organization.

Key Responsibilities:

1. Data Analysis: Collect, clean, and preprocess data from various sources to create datasets for analysis.
2. Statistical Analysis: Apply statistical methods to analyze data and identify trends, patterns, and correlations.
3. Machine Learning: Develop and implement machine learning models to solve business problems and make predictions.
4. Data Visualization: Create informative data visualizations to communicate findings effectively.
5. Collaboration: Work closely with cross-functional teams to understand their data needs and provide insights and solutions.
6. Model Evaluation: Evaluate model performance and iterate on machine learning algorithms to improve accuracy and efficiency.
7. Documentation: Maintain clear and organized documentation of data, models, and analysis methodologies.
8. Stay Current: Stay updated on the latest developments in data science, machine learning, and relevant tools and technologies.

Qualifications:

• Bachelor's degree in a quantitative field such as Computer Science, Data Science, Statistics, or a related discipline.
• Strong analytical and problem-solving skills.
• Proficiency in programming languages such as Python or R.
• Familiarity with data analysis and machine learning libraries (e.g., Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch).
• Good understanding of statistical concepts and hypothesis testing.
• Excellent communication and teamwork skills.
• Eagerness to learn and adapt in a dynamic and fast-paced environment.

Preferred Qualifications:

• Experience with data visualization tools like Matplotlib, Seaborn, or Tableau.
• Knowledge of SQL for data manipulation and extraction.
• Exposure to big data technologies and distributed computing (e.g., Hadoop, Spark).
• Previous experience with cloud platforms such as AWS, Azure, or Google Cloud.
• A solid foundation in deep learning and neural networks.