Job Title: Data Scientist I / Junior Data Scientist

About the Role

We are seeking a motivated and detail-oriented Junior Data Scientist to join our growing data science team. This is an excellent opportunity for recent graduates or early-career professionals who are passionate about data and eager to grow their skills in a collaborative, fast-paced environment.

As a Data Scientist I, you will work under the guidance of senior data scientists and contribute to real-world projects by performing data analysis, building basic models, and supporting decision-making across the business. You will gain hands-on experience with cutting-edge tools and learn how data science drives innovation and strategy.

Key Responsibilities

• Perform data cleaning, preprocessing, and exploratory data analysis (EDA) to prepare datasets for modeling
• Build and validate basic statistical or machine learning models (e.g., linear regression, logistic regression, decision trees) under supervision
• Conduct A/B testing and interpret results to support product or business decisions
• Develop data visualizations and dashboards to communicate insights effectively
• Write well-documented, reusable, and reproducible code using version control tools (e.g., Git)
• Assist in preparing reports and presentations for internal stakeholders
• Collaborate with senior data scientists and business analysts to deliver analytics solutions
• Stay up to date with emerging data tools, technologies, and best practices

Required Qualifications

Education:

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field
• Candidates with a Master’s degree in the above disciplines are encouraged to apply

Skills & Competencies

• Programming: Proficient in Python or R for data analysis and modeling
• SQL: Ability to write queries for data extraction and manipulation
• Statistics: Understanding of statistical concepts such as hypothesis testing, confidence intervals, and distributions
• Machine Learning: Familiarity with supervised learning algorithms and model evaluation techniques
• Data Visualization: Experience using Matplotlib, Seaborn, or similar libraries for plotting
• Tools: Exposure to Jupyter Notebooks, Git, and at least one cloud platform (e.g., AWS, GCP, or Azure)
• Soft Skills: Strong attention to detail, willingness to learn, and effective communication and teamwork skills

Preferred Qualifications (Nice to Have):

• Internships, academic projects, or certifications in data science or analytics
• Exposure to BI tools like Tableau, Power BI, or Looker
• Familiarity with pandas, scikit-learn, and NumPy
• Understanding of basic cloud concepts or experience using cloud-hosted Jupyter environments (e.g., Google Colab, SageMaker Studio)