Data Scientist

Job not on LinkedIn

🕒 Yesterday

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

💵 $80k - $100k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 0%

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NeuroHire

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2025

☁️ SaaS

👥 HR Tech

🎯 Recruiter

SaaS • HR Tech • Recruitment

NeuroHire is an all-in-one SaaS "Career Operating System" that combines AI-driven automation with human career specialists to help IT professionals—especially international students and visa-dependent candidates—navigate the U. S. tech job market. The platform automates job discovery, resume and ATS optimization, large-scale application management, and company-specific interview preparation while human experts verify submissions, provide cultural and visa-aware guidance, and deliver coaching. NeuroHire positions itself as a human+AI symbiosis validated in a pilot program to deliver interview invites and job offers for IT candidates seeking U. S. roles.

📋 Description

• Collect, clean, process, and analyze large datasets from multiple sources. • Perform exploratory data analysis to identify distributions, relationships, trends, and business opportunities. • Develop, train, test, and evaluate machine learning models. • Apply statistical techniques and mathematical methods to support evidence-based decisions. • Write efficient Python code using Pandas, NumPy, Scikit-learn, and Matplotlib. • Build predictive, classification, regression, clustering, and other machine learning solutions. • Use SQL databases to extract, manipulate, and analyze structured data. • Create data visualizations, reports, and presentations communicating analytical findings. • Evaluate model performance and recommend improvements. • Collaborate with software engineers, data analysts, and cross-functional teams to translate business requirements into analytical solutions. • Assist with data processing and machine learning workflows. • Maintain documentation of datasets, methodologies, experiments, and model results. • Stay updated on data science techniques, machine learning technologies, and industry best practices.

🎯 Requirements

• Master's degree in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, or a related technical field. • 0–1 year of experience in Data Science, Machine Learning, Data Analytics, or a related technical role. • Strong programming knowledge in Python and familiarity with Pandas, NumPy, and Scikit-learn. • Solid understanding of statistics, probability, linear algebra, and mathematical fundamentals. • Familiarity with supervised and unsupervised learning. • Understanding of data preprocessing, data cleaning, feature engineering, and exploratory data analysis. • Proficiency in SQL for querying, joining, filtering, and analyzing datasets. • Familiarity with Matplotlib, Seaborn, or Plotly. • Understanding of regression, decision trees, random forests, clustering, and classification. • Familiarity with Jupyter Notebook, Google Colab, or similar development environments. • Basic understanding of model evaluation, validation techniques, and performance metrics. • Familiarity with Git and GitHub for version control and collaborative development. • Strong analytical thinking, critical reasoning, and problem-solving abilities. • Ability to interpret complex data and communicate findings clearly. • Strong attention to detail, teamwork, and willingness to learn new technologies. • Preferred: academic projects, internships, or personal projects involving data science, machine learning, or predictive analytics. • Preferred: familiarity with TensorFlow or PyTorch. • Preferred: basic understanding of NLP and generative AI concepts. • Preferred: exposure to AWS, Microsoft Azure, or Google Cloud Platform. • Preferred: familiarity with model deployment, APIs, or machine learning pipelines. • Preferred: experience participating in data science competitions or working with real-world datasets.

🏖️ Benefits

• Opportunity to contribute to an innovative, AI-powered technology company. • Hands-on exposure to real-world data science and machine learning projects. • Opportunities to strengthen programming, statistical analysis, and machine learning skills. • Collaborative environment that encourages experimentation, innovation, and continuous learning. • Opportunities for professional development and technical career growth. • Exposure to modern data science tools, technologies, and analytical workflows. • Opportunity to contribute to data-driven solutions and meaningful business initiatives.

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