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Entry Level Data Scientist Jobs in Edison, NJ (NOW HIRING)

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Big Data Engineer

New York, NY · On-site

$30 - $40/hr

Entry-Level Data Engineer Job Title: Entry-Level Data Engineer Location: Candidate must be open ... You will work closely with data engineers, analysts, data scientists, and software developers to ...

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Associate Data Scientist

Manhattan, NY · On-site

$64K - $65K/yr

We are seeking an Associate Data Scientist for this entry-level role. You will work to support the team in building ML-powered analyses and products that shape business strategy, optimize content ...

Perform data analysis to support internal and external project needs. Design basic programs for ... Bachelor's/Master's degree, preferably in Computer Science, Information Technology, Computer ...

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Entry Level Data Scientist information

See Edison, NJ salary details

$47.6K

$170.8K

$252.1K

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

As of Aug 1, 2026, the average yearly pay for entry level data scientist in Edison, NJ is $170,835.00, according to ZipRecruiter salary data. Most workers in this role earn between $138,200.00 and $176,000.00 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 are the most commonly searched types of Data Scientist jobs in Edison, NJ? The most popular types of Data Scientist jobs in Edison, NJ are:
What are popular job titles related to Entry Level Data Scientist jobs in Edison, NJ? For Entry Level Data Scientist jobs in Edison, NJ, the most frequently searched job titles are:
What cities near Edison, NJ are hiring for Entry Level Data Scientist jobs? Cities near Edison, NJ with the most Entry Level Data Scientist job openings:
Infographic showing various Entry Level Data Scientist job openings in Edison, NJ as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $170,835 per year, or $82.1 per hour.

Big Data Engineer

Tech Consulting

New York, NY • On-site

$30 - $40/hr

Full-time

Medical, PTO

Posted yesterday

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Job description

Entry-Level Data Engineer

Job Title: Entry-Level Data Engineer

Location: Candidate must be open relocate.

Employment Type: Full-time

Job Summary

We are looking for a motivated Entry-Level Data Engineer to join our data team. In this role, you will help design, build, and maintain data pipelines that support analytics, reporting, and business operations. You will work closely with data engineers, analysts, data scientists, and software developers to ensure data is accurate, reliable, and accessible.

This position is ideal for recent graduates or candidates with internship or project experience in data engineering, computer science, or related fields.

Key Responsibilities

  • Assist in developing and maintaining ETL/ELT data pipelines.
  • Collect, clean, transform, and validate data from multiple sources.
  • Support the design and optimization of databases and data warehouses.
  • Monitor data pipeline performance and troubleshoot issues.
  • Write efficient SQL queries to extract and analyze data.
  • Collaborate with cross-functional teams to understand data requirements.
  • Document data workflows, processes, and technical specifications.
  • Participate in code reviews and follow engineering best practices.
  • Help automate routine data processing tasks.
  • Ensure data quality, integrity, and security.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
  • Basic understanding of SQL and relational databases.
  • Familiarity with at least one programming language such as Python, Java, or Scala.
  • Knowledge of data structures and algorithms.
  • Understanding of ETL/ELT concepts and data modeling fundamentals.
  • Strong analytical and problem-solving skills.
  • Good communication and teamwork abilities.
  • Willingness to learn new technologies and tools.

Preferred Qualifications

  • Internship or academic project experience in data engineering or analytics.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
  • Exposure to big data technologies like Apache Spark or Hadoop.
  • Experience with version control systems such as Git.
  • Knowledge of workflow orchestration tools (e.g., Apache Airflow).
  • Basic understanding of data warehousing concepts.

Technical Skills

  • SQL
  • Python (preferred)
  • Git
  • Relational databases (PostgreSQL, MySQL, SQL Server, etc.)
  • Basic Linux/Unix commands
  • Excel
  • Cloud fundamentals (AWS, Azure, or GCP)

Soft Skills

  • Problem-solving mindset
  • Attention to detail
  • Communication skills
  • Team collaboration
  • Time management
  • Adaptability
  • Eagerness to learn

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