Senior Data Scientist

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

This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title: Senior Data Scientist

Location: 100% Remote (U.S.)

Position Type: Full-time, Direct W2

Salary Range: $160,000–$180,000 Annually

Experience

Required:

6+ years

Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

We are seeking an accomplished Senior Data Scientist to design, develop, deploy, and optimize enterprise-grade data science and machine learning solutions that support strategic business initiatives across multiple domains. In this role, you will be responsible for the complete data science lifecycle, from translating business problems into analytical solutions and developing predictive models to deploying machine learning pipelines, monitoring model performance, and supporting data-driven decision-making throughout the operational lifecycle.

The successful candidate will bring deep expertise in statistical analysis, machine learning, predictive modeling, and data engineering, combined with strong hands-on experience working with large-scale structured and unstructured datasets using modern analytics platforms and cloud technologies. You will work closely with business stakeholders, data engineers, software developers, product managers, and cross-functional teams in an Agile environment to deliver scalable, accurate, and impactful data science solutions that directly support strategic business outcomes.

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a closely related quantitative discipline.
• Five or more years of professional experience developing production-grade machine learning models, predictive analytics solutions, and enterprise data science applications.
• Strong, demonstrable understanding of statistics, probability, machine learning algorithms, data structures, data modeling, feature engineering, model evaluation techniques, and end-to-end machine learning lifecycle principles.
• Advanced working knowledge of Python, R, SQL, Scikit-learn, Tensor Flow, PyTorch, Pandas, Num Py, and modern data science libraries for building scalable analytical solutions.
• Hands-on, production-level experience designing, training, validating, deploying, and monitoring machine learning models, including regression, classification, clustering, forecasting, recommendation systems, and natural language processing applications.
• Proven experience working with relational and No
  
  SQL databases, large-scale datasets, data warehouses, and distributed data processing platforms such as Spark, Hadoop, Snowflake, Databricks, or Big Query.
• Strong SQL skills and meaningful experience performing data exploration, feature engineering, query optimization, ETL development, data visualization, and business intelligence reporting using enterprise data platforms.
• Solid experience with Git-based version control workflows, CI/CD processes, MLOps practices, model deployment pipelines, code review processes, and collaborative software development methodologies.
• Hands-on experience deploying machine learning solutions on at least one major cloud platform (AWS, Azure, or GCP), including managed AI/ML services, storage, networking, and identity management capabilities.
• Strong debugging, analytical thinking, problem-solving, and root-cause analysis skills, with the discipline to investigate complex data…