Data Scientist Specialist - Remote

Overview

You’ll design and implement data science and machine learning solutions that blend cutting-edge research with practical deployment. Working across industries, domains, and use cases, you’ll tackle challenging analytical problems, build robust models, and deliver insights that power client-facing tools and internal platforms.

In Short

• Develop End-to-End Models: Design, train, and evaluate models for prediction, classification, optimization, or inference—taking projects from exploratory analysis through production deployment.
• Collaborate on Real-World Solutions: Partner with software engineers, analysts, and fellow data scientists to integrate data-driven models into scalable, deployable systems that operate in dynamic production environments.
• Client-Focused Problem Solving: Work closely with stakeholders to frame ambiguous problems, explore solution paths, and translate complex technical insights into clear, actionable recommendations.
• Explore, Iterate, Validate: Lead the exploration and analysis of large and diverse datasets using tools like Pandas, NumPy, and Spark to inform model design, evaluate performance, and identify opportunities for improvement.
• Research-Driven Innovation: Stay current with advances in statistics, machine learning, and data engineering practices—adapting new methods and technologies to deliver measurable impact on real-world problems.

Requirements

• 2+ years of hands-on experience building and deploying data science or machine learning models in production environments.
• Proven ability to take models from prototype to production using Python-based workflows.
• Experience engaging with technical and non-technical stakeholders to refine requirements and communicate results effectively.
• Strong proficiency in Python and commonly used ML/data libraries (Pandas, NumPy, scikit-learn, PyTorch, or similar).
• Experience working with large-scale datasets and distributed tools such as Spark.
• Comfort navigating cloud environments (e.g., GCP, AWS, or similar); Databricks experience is a plus.
• Solid understanding of statistical modeling, experimental design, model evaluation, and data debugging practices.
• Strong code hygiene — able to write clean, modular, and testable code in collaborative, version-controlled environments.

Benefits

• Competitive pay rate based on experience and expertise.
• Opportunity to work on diverse projects across various industries.
• Flexible working arrangements as a contractor.
• Gain experience with cutting-edge tools and technologies in data science.
• Collaborate with a talented team of professionals.