Entry-Level Data Scientist

Entry-Level Data Scientist

Full-Time

Candidate must be open to relocate.

Position Overview

We are seeking an enthusiastic and analytical Entry-Level Data Scientist with strong Python programming skills to join our data science team. The ideal candidate will have a foundation in data analysis, statistics, machine learning, and Python, and will be eager to apply these skills to real-world business problems.

You will work with experienced data scientists, engineers, and business stakeholders to collect, clean, analyze, and model data and help develop data-driven solutions.

Key Responsibilities

• Collect, clean, transform, and analyze structured and unstructured datasets.
• Use Python to perform data analysis, automation, and statistical modeling.
• Develop and evaluate basic machine learning models for classification, regression, clustering, and prediction problems.
• Work with libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib/Seaborn.
• Perform exploratory data analysis (EDA) and identify trends, patterns, and anomalies.
• Prepare data and features for machine learning models.
• Evaluate model performance using appropriate statistical and machine learning metrics.
• Create visualizations and communicate findings to technical and non-technical stakeholders.

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• Write clean, maintainable, and well-documented Python code.
• Collaborate with data engineers and software developers to integrate analytical solutions into applications or data pipelines.
• Assist with experimentation, A/B testing, and statistical analysis.
• Stay current with data science, machine learning, and analytics techniques.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• Strong programming skills in Python.
• Knowledge of Pandas, NumPy, Scikit-learn, and basic data visualization libraries.
• Understanding of fundamental statistics and probability.
• Knowledge of machine learning concepts and algorithms.
• Experience working with SQL and relational databases.
• Ability to clean, manipulate, and analyze datasets.
• Strong problem-solving and analytical skills.
• Ability to communicate technical findings clearly.
• Preferred Qualifications
• Internship, academic, or personal project experience in data science or machine learning.
• Familiarity with Jupyter Notebook and Git/GitHub.

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• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
• Exposure to data visualization tools such as Power BI or Tableau.
• Understanding of APIs, data pipelines, or basic software engineering practices.

Technical Skills

• Programming: Python, SQL
• Data Analysis: Pandas, NumPy
• Machine Learning: Scikit-learn
• Visualization: Matplotlib, Seaborn, Plotly
• Databases: SQL, relational databases
• Tools: Jupyter Notebook, Git/GitHub
• Concepts: Statistics, probability, EDA, feature engineering, model evaluation, supervised and unsupervised learning

What We’re Looking For

We are looking for someone who enjoys solving problems with data, has strong Python coding fundamentals, and is motivated to learn. Candidates should be comfortable working independently on smaller analytical tasks while collaborating with senior team members on larger data science projects.

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