Entry-Level Data Scientist

SharpAtoms; United States; On-site; USD 65,000 - 90,000; Full time

Job summary

SharpAtoms is seeking an entry-level Data Scientist to analyze data, build introductory machine learning models, and turn findings into clear recommendations. This role is designed for candidates starting their data science journey and will partner with experienced teammates to grow skills.

Ideal candidates have 0-1 year of relevant experience or strong project work, and a foundation in Python, SQL, statistics, and data visualization. Collaboration with cross-functional teams is essential.

Qualifications

• 0-1 year of full-time professional data science or analytics experience.
• Academic projects, internships, bootcamp projects, personal projects, GitHub portfolios, and research experience are valued.
• Candidates with more than 1 year of relevant full-time experience may be better suited for experienced-level roles.

Responsibilities

• Collect, clean, validate, and explore structured data.
• Use Python and SQL to identify patterns, trends, and data quality issues.
• Document data sources, assumptions, and analysis steps.
• Apply basic statistical methods to answer business questions.
• Assist in building, testing, and evaluating machine learning models for tasks such as classification, regression, or forecasting.
• Compare model results using evaluation metrics and explain limitations.
• Create charts, reports, and presentations that make findings understandable to technical and non-technical audiences.
• Communicate insights and recommendations to stakeholders.
• Work with senior data scientists, analysts, engineers, and business teams.
• Participate in project reviews, incorporate feedback, and continue developing technical skills.

Skills

Python

Pandas

NumPy

SQL

Data Visualization

Machine Learning basics

Jupyter/Colab

Git

Education

Bachelor's or Master's degree in Data Science, CS, Statistics, Math, Engineering or related field

Equivalent practical training and strong project experience

Tools

Pandas

NumPy

Git

Jupyter

Job description

We are looking for a curious and motivated Entry-Level Data Scientist to join our team. This role is designed for candidates beginning their careers in data science. You will work alongside experienced team members to analyze data, build introductory machine learning models, and turn findings into clear recommendations.

Who Should Apply?

This opportunity is intended for candidates with 0-1 year of full-time professional data science or analytics experience.

• No prior full-time professional experience is required.
• Academic projects, internships, bootcamp projects, personal projects, GitHub portfolios, and research experience are valued.
• Candidates with more than 1 year of relevant full-time experience may be better suited for experienced-level roles.

Key Responsibilities

Data Analysis & Preparation

• Collect, clean, validate, and explore structured data.
• Use Python and SQL to identify patterns, trends, and data quality issues.
• Document data sources, assumptions, and analysis steps.
• Apply basic statistical methods to answer business questions.
• Assist in building, testing, and evaluating machine learning models for tasks such as classification, regression, or forecasting.
• Compare model results using appropriate evaluation metrics and explain limitations.
• Create charts, reports, and presentations that make findings understandable to technical and non-technical audiences.
• Communicate insights and recommendations to stakeholders.
• Work with senior data scientists, analysts, engineers, and business teams.
• Participate in project reviews, incorporate feedback, and continue developing technical skills.

Required Skills & Qualifications:

Education:

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• Equivalent practical training and strong project experience may also be considered.

Experience

0-1 year of full-time professional data science or analytics experience.

Technical Skills:

• Working knowledge of Python, including Pandas and NumPy.
• Basic SQL skills for querying and combining data.
• Understanding of data cleaning, exploratory data analysis, and visualization.
• Foundational knowledge of statistics, including distributions, sampling, and hypothesis testing.
• Familiarity with machine learning concepts such as train/test splits, regression, classification, and model evaluation.
• Experience with notebooks such as Jupyter or Google Colab.
• Familiarity with Git/GitHub is a plus.

Soft Skills:

• Strong analytical thinking and problem-solving skills.
• Ability to explain findings clearly and acknowledge uncertainty.
• Good communication and collaboration skills.
• Willingness to learn and seek feedback.

Equal Opportunity Employer:

We are an Equal Opportunity Employer. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.