Junior Data Scientist (Entry-Level) 

 Location: Remote

Employment Type: Full-Time
Experience Level: 0–2 Years (entry level candidates & Entry-Level Candidates Welcome)

About the Role

We are seeking a highly motivated Junior Data Scientist to join our growing analytics team. This role is designed for recent STEM graduates, international students on OPT/CPT, and early-career professionals who are eager to apply data science concepts to real-world, production-level business problems.

You will work closely with senior data scientists, data engineers, and business stakeholders on U.S.-based client projects, gaining hands-on exposure to the complete data science lifecycle—from data acquisition to model deployment and insights delivery.

Key Responsibilities

Data Analysis & Preparation

• Collect, clean, validate, and preprocess structured and semi-structured datasets
• Handle missing data, outliers, and data inconsistencies using statistical techniques
• Perform Exploratory Data Analysis (EDA) to identify trends, patterns, and anomalies

Statistical & Machine Learning Work

• Apply descriptive and inferential statistics to support data-driven decisions
• Build, train, and evaluate machine learning models, including:
  • Regression (Linear, Logistic)
  • Classification (Decision Trees, Random Forest, XGBoost – basic exposure)
  • Clustering (K-Means, Hierarchical)
• Perform feature engineering and feature selection
• Evaluate models using metrics such as accuracy, precision, recall, F1-score, ROC-AUC, RMSE

Programming & Data Engineering Support

• Write clean, efficient, and reusable Python code for analysis and modeling
• Develop and optimize SQL queries involving joins, subqueries, aggregations, and window functions
• Work with Jupyter Notebooks and version control systems (Git/GitHub)

Visualization & Reporting

• Create meaningful visualizations and dashboards using tools such as Matplotlib, Seaborn, Tableau, or Power BI
• Present analytical findings to technical and non-technical stakeholders
• Prepare documentation, reports, and model summaries for internal and client use

Collaboration & Learning

• Collaborate with senior data scientists, ML engineers, and data engineers
• Participate in code reviews, model reviews, and technical discussions
• Continuously learn new tools, algorithms, and industry best practices

Required Technical Skills

Programming & Tools

• Python: Pandas, NumPy, Scikit-learn
• SQL: Complex joins, subqueries, aggregations
• Data Tools: Jupyter Notebook, Git/GitHub

Data Science Fundamentals

• Strong understanding of Statistics & Probability
• Solid foundation in Machine Learning concepts
• Data cleaning, preprocessing, and feature engineering techniques
• Model evaluation and validation concepts

Nice to Have / Preferred Skills

• Data visualization tools: Tableau, Power BI, Looker
• Cloud exposure: AWS (S3, EC2), Azure, or Google Cloud Platform
• Big data basics: Spark / PySpark
• Deep learning fundamentals: TensorFlow or PyTorch
• Familiarity with REST APIs and basic data pipelines

Education Requirements

• Bachelor’s or Master’s degree in a STEM discipline, such as:
  • Data Science
  • Computer Science
  • Statistics
  • Engineering
  • Mathematics or related fields

Visa & Work Authorization

• H-1B sponsorship available for eligible candidates
• STEM OPT / CPT candidates strongly encouraged to apply
• Open to international students and entry level candidates

Why Join Us

• Hands-on experience with real U.S. client projects
• Structured mentorship from senior data scientists
• Clear career growth path toward Data Scientist / ML Engineer roles
• Exposure to enterprise-level datasets and tools
• Inclusive, diverse, and learning-driven work cultur