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Entry Level Data Scientist Ibm Jobs (NOW HIRING)

Altamira Technologies Corp.

Data Scientist

Tampa, FL · On-site

Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake.

IBM

NC · On-site

Introduction At IBM, work is more than a job - it's a calling: To build. To design. To code. To ... Data Science development team. As a Junior Developer, you will contribute to the design ...

Socket.dev

Data Scientist

Tampa, FL · On-site

$125 - $150/hr

Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake.

Arcfield

Data Scientist I

Chantilly, VA · On-site

Responsibilities Arcfield is looking for an entry-level DATA SCIENTISTS to serve as an essential member of a team responsible for transforming raw data into meaningful insights and tools that improve ...

New

IBM

Associate Data Engineer 2027 - AI & Analytics

Lansing, MI · On-site

$59K - $60K/yr

At IBM, AI is part of how we deliver solutions, accelerate development, analyze data, automate ... Work side-by-side with experienced consultants, data engineers, data scientists, AI specialists ...

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

As of Sep 7, 2026, the average yearly pay for entry level data scientist ibm 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 at IBM do?

An Entry Level Data Scientist at IBM is responsible for analyzing large datasets, building predictive models, and generating insights to help solve business problems. They work with a team to clean and preprocess data, apply machine learning algorithms, and communicate findings to stakeholders. This role often involves using programming languages like Python or R, and tools such as Jupyter Notebook, SQL, and IBM's own data science platforms. Entry-level data scientists gain valuable experience collaborating on real-world projects while learning from experienced professionals.

What are the key skills and qualifications needed to thrive as an entry level data scientist at IBM?

To thrive as an Entry Level Data Scientist at IBM, you need a solid background in statistics, programming (Python or R), and data analysis, usually supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning libraries (such as scikit-learn or TensorFlow), data visualization tools, and experience using platforms like IBM Cloud or Watson is highly valued. Strong problem-solving abilities, curiosity, and effective communication skills help you translate data insights into actionable business solutions. These skills are crucial for delivering impactful data-driven recommendations and collaborating with diverse teams in a fast-paced, innovative environment.

What opportunities for mentorship and skill development are available to entry level data scientists at IBM?

As an entry-level data scientist at IBM, you can expect to benefit from a structured mentorship program where experienced data scientists guide you through projects and technical challenges. IBM also offers access to a wide range of internal training resources, including online courses, workshops, and seminars covering the latest tools and methodologies in data science. Collaboration is highly encouraged, with frequent team meetings and cross-functional projects that provide exposure to real-world business problems and diverse teams. This supportive environment helps new hires learn industry best practices while rapidly expanding their technical and professional skill sets.

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

AspectEntry Level Data Scientist IbmEntry Level Data Analyst Ibm
Required CredentialsBachelor's in CS, Statistics, or related field; some roles prefer certifications in data science or analyticsBachelor's in Business, Economics, or related field; certifications in Excel, SQL, or data analysis tools are common
Work EnvironmentCollaborative teams in tech or consulting firms, focusing on advanced analytics and modelingBusiness units or IT teams, focusing on data reporting, visualization, and basic analysis
Employer & Industry UsageTech companies, consulting firms, finance, healthcareRetail, finance, healthcare, and corporate sectors

Entry Level Data Scientist Ibm focuses on developing predictive models and advanced analytics, requiring stronger technical skills. Entry Level Data Analyst Ibm emphasizes data reporting, visualization, and basic analysis. Both roles are essential but differ in complexity and technical depth.

Can I get an entry level data scientist job with no experience?

Entry level data scientist positions typically require some foundational knowledge of programming languages like Python or R, and familiarity with data analysis tools and techniques. While prior work experience is not always mandatory, demonstrating relevant skills through projects, coursework, or certifications can improve chances of hiring. Employers often look for candidates with a strong understanding of statistics, machine learning, and data visualization.

Does IBM have entry-level data scientist positions?

IBM offers entry-level data scientist positions that typically require skills in data analysis, programming languages like Python or R, and familiarity with machine learning tools. These roles often target recent graduates or those with limited professional experience and may include training or mentorship programs.

What is the salary of entry level data scientist in IBM?

The average starting salary for an entry-level data scientist at IBM is approximately $85,000 to $95,000 per year, depending on location and educational background. Salaries can vary based on skills, certifications, and the specific role within the company.

What cities are hiring for Entry Level Data Scientist Ibm jobs?

Cities with the most Entry Level Data Scientist Ibm job openings:

What are the most commonly searched types of Data Scientist Ibm jobs?

The most popular types of Data Scientist Ibm jobs are:

What states have the most Entry Level Data Scientist Ibm jobs?

States with the most job openings for Entry Level Data Scientist Ibm jobs include:

Entry Level Data Scientist Ibm jobs near you

Data Scientist - Fraud Detection

DataVisor

Mountain View, CA • On-site

Full-time

Medical, PTO

Posted 11 days ago

Key responsibilities

  • Develop and deploy machine learning models for fraud detection and risk assessment.

  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.

  • Collaborate with engineering and business teams to integrate ML models into production systems.

Job description

About DataVisor:
DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.

Key Responsibilities:

  • Develop and deploy machine learning models for fraud detection and risk assessment.
  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.
  • Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.).
  • Collaborate with engineering and business teams to integrate ML models into production systems.
  • Continuously monitor model performance and refine algorithms to improve accuracy.
  • Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies.

Requirements

  • Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus. 
  • Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus).
  • Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.).
  • Experience with SQL and data manipulation/analysis in large datasets.
  • Strong problem-solving skills and patience for deep-dive data exploration.
  • Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus.
  • Excellent communication skills and ability to work in a collaborative environment.
Nice to have
  • Familiarity with big data tools (Spark, Hadoop, Dask).
  • Knowledge of graph-based fraud detection techniques.
  • Experience with cloud platforms (AWS, GCP, Azure).

Benefits

PTO, Stock Option, Health Benefits