Senior Data Scientist (AI)

Location: 100% remote within the United States

Salary: $160,000–$180,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

• Translate business problems into analytical solutions and predictive models.
• Design, train, validate, deploy, and optimize production-grade machine learning models.
• Build and maintain machine learning pipelines, including model monitoring and lifecycle support.
• Work with large-scale structured and unstructured datasets, data warehouses, and distributed processing platforms.
• Collaborate with business stakeholders, data engineers, software developers, product managers, and cross-functional Agile teams.
• Communicate findings and translate analytical insights into actionable business recommendations.

Requirements

• Bachelor’s degree in data science, computer science, statistics, mathematics, engineering, artificial intelligence, or a related quantitative discipline.
• At least 5 years of professional experience developing production machine learning models, predictive analytics solutions, and enterprise data science applications; the posting specifies 6+ years of experience.
• Strong knowledge of statistics, probability, machine learning algorithms, data modeling, feature engineering, model evaluation, and the end-to-end machine learning lifecycle.
• Advanced experience with Python, R, SQL, Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, relational and NoSQL databases, and large-scale datasets.
• Experience with cloud deployment on AWS, Azure, or GCP, as well as Git workflows, CI/CD, MLOps, model deployment pipelines, code reviews, and collaborative software development.
• Applicants must be able to work remotely from the United States. U.S. citizens, Green Card holders, EAD holders, and H-1B transfer candidates are encouraged to apply; new H-1B visa petitions cannot be sponsored.

Nice to have

• Experience with real-time machine learning, recommendation engines, streaming analytics, event-driven architectures, Kafka, or Spark Streaming.
• Familiarity with Docker, Kubernetes, Kubeflow, MLflow, Airflow, feature stores, experiment tracking, and model monitoring.
• Exposure to deep learning, reinforcement learning, computer vision, generative AI, large language models, explainable AI, model fairness, and responsible AI.

Culture & Benefits

• Full-time direct W-2 employment.
• Fully remote work arrangement within the United States.
• Work in an Agile environment with cross-functional collaboration.
• Career growth opportunities within an established technology consulting and software development organization.