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Entry Level Data Scientist Jobs (NOW HIRING)

Collaborate closely with data analysts, data engineers, and business and project stakeholders to incorporate their expertise into data science solutions. * Present and defend results to leadership ...

Data Scientist - NYC

Boston, MA · On-site

$100 - $200/hr

Experience with machine learning or adjacent fields (natural language processing, random forests, linear regression, predictive modeling, and entry-level data science concepts) * Experience writing ...

This is an entry level Data Scientist Role for a person who is self motivated and has a passion to innovate and work on cutting edge technology. Qualifications Candidate should have experience in ...

This is an entry level Data Scientist Role for a person who is self motivated and has a passion to innovate and work on cutting edge technology. Qualifications Candidate should have experience in ...

... scientists who research and integrate algorithms to develop an application, software, and computer system solutions to address complex data problems Assess project requirements and develop data ...

As a Data Scientist in our organization, you will play a crucial role in disrupting current ... Job Schedule Full time Job Number R000135859 Job Segmentation Entry Level Starting Pay / Salary ...

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How much do entry level data scientist jobs pay per year?

As of Jun 18, 2026, the average yearly pay for entry level data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What Does an Entry-Level Data Scientist Do?

An entry-level data scientist works to examine, interpret, and collect large sets of data. In this role, your responsibilities include extracting and processing information to find patterns and trends, using technology to analyze data, and creating a machine-learning algorithm or predictive model for data analysis. Other duties include proposing strategies and solutions based on the information you derived from a data set, using ensemble modeling to combine models, automating processes to collect data, discovering valuable data sources, and using data visualization techniques to present information. You often collaborate with product development and engineering teams.

What does an Entry Level Data Scientist do?

An Entry Level Data Scientist helps organizations analyze and interpret large sets of data to solve business problems. They typically assist with data cleaning, exploratory data analysis, and building simple machine learning models under the supervision of more experienced data scientists. Their work often involves using programming languages like Python or R, and tools such as SQL and data visualization software. Entry level data scientists also collaborate with other team members to communicate findings and support data-driven decision-making.

What are some typical challenges faced by entry level data scientists in their first year on the job?

Entry level data scientists often encounter challenges such as working with messy or incomplete datasets, adapting to unfamiliar data tools and company-specific processes, and translating business problems into actionable data analyses. They may also find it challenging to communicate technical findings to non-technical stakeholders and to prioritize projects in a fast-paced environment. Building strong relationships with colleagues in engineering, business, and analytics teams is key to overcoming these challenges and accelerating learning.

What are the key skills and qualifications needed to thrive as an Entry Level Data Scientist, and why are they important?

To thrive as an Entry Level Data Scientist, you need a solid foundation in statistics, programming (typically Python or R), and data analysis, often supported by a degree in a quantitative field such as mathematics, computer science, or engineering. Familiarity with tools like SQL, Jupyter Notebooks, and machine learning libraries (e.g., scikit-learn, TensorFlow) is commonly expected. Strong problem-solving skills, curiosity, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These abilities enable you to extract actionable insights from data, support business decisions, and contribute value to data-driven organizations.

What is the difference between Entry Level Data Scientist vs Data Analyst?

AspectEntry Level Data ScientistData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Business, Statistics, or related field; strong Excel, SQL, and visualization skills
Work EnvironmentCollaborates with data science teams, uses programming languages like Python or R, focuses on predictive modelingWorks with business teams, uses SQL, Excel, and BI tools, focuses on reporting and data visualization
Employer & Industry UsageTech companies, finance, healthcare, startupsRetail, marketing, finance, healthcare, government

Entry Level Data Scientists and Data Analysts often share foundational skills like SQL and data visualization. However, data scientists typically focus on building predictive models and machine learning algorithms, requiring programming knowledge, while data analysts concentrate on interpreting data through reports and dashboards. Both roles are essential in data-driven organizations but differ in technical depth and project scope.

What cities are hiring for Entry Level Data Scientist jobs? Cities with the most Entry Level Data Scientist job openings:
What are the most commonly searched types of Data Scientist jobs? The most popular types of Data Scientist jobs are:
What states have the most Entry Level Data Scientist jobs? States with the most job openings for Entry Level Data Scientist jobs include:
Entry Level Data Scientist

Full-time

Posted 5 days ago


Job description

Job Description
  • Work closely with engineering and marketing teams to identify and answer important product questions to drive business growth.
  • Create machine learning solutions for a diverse set of business problems.
  • Employ structured approaches to leveraging large data sets to uncover new insights.
  • Collaborate closely with data analysts, data engineers, and business and project stakeholders to incorporate their expertise into data science solutions.
  • Present and defend results to leadership audiences, both technical and non-technical.
  • Our team philosophy encourages knowledge sharing so you will contribute to the research community through technical papers and presentations published both internally and externally.
Tech Stack
  • SQL
  • Python
  • Jupyter Notebook
  • (Optional) R script
Experience & Qualifications
  • Passion in modern technology and ability to work in a start-up environment.
  • Efficient on Jupyter Notebook
  • Good mathematic and algorithm background
  • Strong influencing skills essential. Capable of assertively interacting with business stakeholders and counterparts in order to resolve day to day issues.
  • Highly organized individual with attention to detail and excellent ability to execute on deliverables.
Employment Type: FULL_TIME