Junior Data Scientist

DetaPent; South Carolina; Remote; USD 60,000 - 90,000; Full time

Job summary

A technology company is seeking a Jr. Data Scientist / AI-ML Engineer to develop and optimize models for anomaly detection. This remote position requires strong programming skills, a degree in a relevant field, and the ability to collaborate with both technical and business teams. Ideal candidates have experience with machine learning techniques and deploying models into production.

Qualifications

• 1+ years of hands-on experience in data science, AI, or ML engineering.
• Solid understanding of Data Science with a heavy focus on statistical modeling and Machine Learning.
• Experience with anomaly detection techniques — supervised, unsupervised, and hybrid approaches.

Responsibilities

• Collaborate with stakeholders to define requirements for anomaly detection.
• Develop, optimize, and maintain computational models for anomaly detection using AI/ML techniques.
• Design and implement statistical models to enhance anomaly detection accuracy.

Skills

Proficiency in Python

Data Analysis

Machine Learning Algorithms

Statistical Modeling

Problem-solving skills

Education

Bachelor’s or master’s degree in computer science, Data Science, Statistics, Mathematics

Tools

NumPy

Pandas

Scikit-learn

PyTorch

TensorFlow

SQL

Spark

Job description

This range is provided by DetaPent. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$60,000.00/yr - $90,000.00/yr

Title: Jr. Data Scientist / AI-ML Engineer

Location: Columbia, SC (Remote)

Duration: Full Time

Responsibilities

• Collaborate with stakeholders to understand business objectives and define requirements for anomaly detection.
• Develop, optimize, and maintain computational models for debit transaction anomaly detection using AI/ML techniques.
• Perform data analysis, generate insights, and identify patterns to support decision-making.
• Design and implement statistical models, including standard deviation calculations, variance thresholds, and probabilistic models to enhance anomaly detection accuracy.
• Work with existing models to apply backtracking methodologies and improve anomaly reduction strategies.
• Leverage machine learning algorithms (e.g., classification, clustering, time-series modeling) to predict, detect, and manage anomalies.
• Collaborate with engineers and business teams to integrate models into production systems.
• Conduct performance monitoring, fine-tuning, and validation of ML models to ensure accuracy and reliability.
• Prepare technical documentation, visualizations, and reports to communicate findings effectively to business and technology stakeholders.

Qualifications

• Bachelor’s or master’s degree in computer science, Data Science, Statistics, Mathematics, or a related field.
• 1+ years of hands-on experience in data science, AI, or ML engineering.
• Strong proficiency in Python, R, or Scala with experience using data science libraries (e.g., NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).
• Solid understanding of Data Science with a heavy focus on statistical modeling and Machine Learning, hypothesis testing, regression analysis, and variance modeling.
• Experience with anomaly detection techniques — supervised, unsupervised, and hybrid approaches.
• Experience in Generative AI based implementations.
• Expertise in working with large datasets using SQL, Spark, or similar data-processing frameworks.
• Strong problem-solving, analytical thinking, and communication skills.
• Experience in deploying ML models into production environments, ML Ops, preferably on AWS.

Regards,

DetaPent

Seniority

• Entry level

Employment type

• Full-time

Industries

• IT Services and IT Consulting