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Data Scientist - Remote

Remote / Online - Candidates ideally in
Columbus, Franklin County, Ohio, 43224, USA
Listing for: Data Freelance Hub
Remote/Work from Home position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Machine Learning/ ML Engineer, AI Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

⭐ - Featured Role | Apply direct with Data Freelance Hub

This role is for a Data Scientist (Remote) with a contract length of unspecified duration and a competitive pay rate. Key requirements include an advanced degree, proficiency in Python and machine learning frameworks, and strong analytical and communication skills.

United States

Remote

Overview

We are looking for a talented and experienced Data Scientist to join our dynamic team. As a Data Scientist, you will leverage your analytical skills and expertise in machine learning to extract insights from complex datasets and drive data‑driven decision‑making across our organization. You will collaborate closely with cross‑functional teams to develop predictive models, uncover actionable insights, and solve challenging business problems.

Responsibilities
  • Data Analysis and Exploration
    • Analyze large, complex datasets to identify trends, patterns, and relationships.
    • Conduct exploratory data analysis (EDA) to gain insights and formulate hypotheses.
    • Utilize statistical methods and data visualization techniques to communicate findings effectively.
  • Predictive Modeling and Machine Learning
    • Develop and deploy predictive models using machine learning algorithms.
    • Perform feature engineering, model selection, and hyper‑parameter tuning to optimize model performance.
    • Evaluate model accuracy, precision, recall, and other performance metrics.
  • Data Mining and Pattern Recognition
    • Apply data mining techniques to extract actionable insights from structured and unstructured data.
    • Identify patterns and anomalies in data to detect fraud, predict customer behavior, or optimize business processes.
    • Implement clustering, classification, regression, and other machine learning algorithms as needed.
  • Experimentation and A/B Testing
    • Design and conduct experiments to test hypotheses and validate model assumptions.
    • Implement A/B testing frameworks to evaluate the impact of changes and interventions.
    • Analyze experimental results and provide recommendations for further optimization.
  • Data Integration and API Development
    • Build and maintain integrations with internal and external data sources and APIs.
    • Implement RESTful APIs and web services for data access and consumption.
    • Ensure compatibility and interoperability between different systems and platforms.
  • Collaboration and Communication
    • Collaborate with cross‑functional teams, including engineers, product managers, and business stakeholders.
    • Translate technical findings into actionable insights and recommendations for non‑technical audiences.
    • Present findings and proposals in clear, concise, and compelling ways.
    • Collaborate with analysts and platform teams; participate in reviews, sprints, POCs, and reusable frameworks.
Requirements
  • Advanced degree (Master's or Ph.D.) in Computer Science, Statistics, Mathematics, Economics, or related field.
  • Proven experience in data science, machine learning, or predictive analytics roles.
  • Proficiency in programming languages commonly used in data science (e.g., Python, PySpark, R).
  • Strong understanding of statistical analysis, hypothesis testing, and experimental design.
  • Experience with machine learning libraries and frameworks (e.g., Tensor Flow, scikit‑learn, PyTorch).
  • Familiarity with data visualization tools and techniques (e.g., Matplotlib, ggplot, Tableau, Power BI).
  • Excellent problem‑solving and analytical skills with attention to detail.
  • Effective communication and collaboration abilities in a team environment.
  • Ability to manage multiple projects and prioritize tasks effectively.
  • Exceptional ability to translate complex AI/ML concepts into clear, actionable insights for both technical and non‑technical stakeholders.
  • Strong collaboration and communication skills to partner effectively with cross‑functional teams including business analysts, engineers, and leadership.
  • Proficient in producing high‑quality technical documentation (design specs, test cases, and user guides) for code and model lifecycle management.
  • Strong problem‑solving and critical thinking abilities, with a focus on innovative, comprehensive solutions.

Equal Opportunity

Employer:

Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

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