Remote opportunity at
Bright Vision TechnologiesSenior Data Scientist
This is a full-time, direct W2 role at Bright Vision Technologies, a US-based firm offering consulting and software development in cloud, AI, data, and enterprise areas.…
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About This Role
This is a full-time, direct W2 role at Bright Vision Technologies, a US-based firm offering consulting and software development in cloud, AI, data, and enterprise areas. The position is fully remote within the United States and carries a stated salary of $160,000 to $180,000 per year. The senior data scientist owns the full data science lifecycle. That covers turning business challenges into analytical work, building predictive models, deploying machine learning…
Job Description
This is a full-time, direct W2 role at Bright Vision Technologies, a US-based firm offering consulting and software development in cloud, AI, data, and enterprise areas. The position is fully remote within the United States and carries a stated salary of $160,000 to $180,000 per year.
The senior data scientist owns the full data science lifecycle. That covers turning business challenges into analytical work, building predictive models, deploying machine learning pipelines, and monitoring model performance once it is live. The work involves large structured and unstructured datasets on modern analytics and cloud platforms, and the person collaborates with business stakeholders, data engineers, developers, and product managers in an Agile setting.
The posting asks for a bachelor's degree in a quantitative subject, with examples including statistics, math, computing, engineering, and applied AI. Expected model work spans classification, forecasting, clustering, recommendation engines, and language processing. Advanced Python, R, and SQL are required, along with hands-on use of libraries such as Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy.
Tooling expectations also include distributed data platforms such as Spark, Snowflake, Databricks, or BigQuery, and hands-on deployment work on a public cloud such as AWS, Azure, or GCP. Production deployment, Git-based workflows, CI/CD, and MLOps practices are part of the day-to-day requirements. Strong SQL, ETL development, and debugging skills round out the core expectations.
Preferred experience includes streaming systems with Kafka or Spark Streaming, containers and orchestration with Docker, Kubernetes, MLflow, or Airflow, and exposure to deep learning, computer vision, generative AI, and large language models.
Responsibilities
- Translate business challenges into analytical solutions and predictive models.
- Deploy machine learning pipelines and monitor model performance after launch.
- Work with large structured and unstructured datasets on modern analytics and cloud platforms.
- Collaborate with business stakeholders, engineers, and product managers in an Agile setting.
- Support data-driven decisions across the operational life of each model.
Requirements
- A bachelor's degree in a quantitative subject such as statistics, math, computing, or engineering.
- Five-plus years of hands-on work putting predictive models and analytics into production systems.
- Solid grasp of statistics and probability, plus ML algorithms and the end-to-end ML lifecycle.
- Advanced Python, R, and SQL, plus common libraries such as Scikit-learn, TensorFlow, and PyTorch.
- Experience deploying, monitoring, and retraining models in production.
- Working knowledge of Spark, Snowflake, Databricks, or BigQuery for large datasets.
- Strong SQL, plus ETL, query optimization, data visualization, and BI reporting experience.
- Familiarity with Git workflows, CI/CD, code review, and MLOps practices.
- Practical deployment on a public cloud such as AWS, Azure, or GCP, using managed AI and ML services.
- Strong debugging and root-cause analysis skills.
- Ability to turn analytical findings into practical business recommendations.
Qualifications
- Experience with real-time ML systems, streaming analytics, or event-driven architectures using Kafka or Spark Streaming.
- Familiarity with container tooling such as Docker, Kubernetes, MLflow, or Airflow.
- Exposure to advanced AI topics, including neural networks, vision models, LLMs, explainability, and model fairness.
- Background in automated testing and experiment tracking, plus feature stores and data governance in enterprise Agile teams.
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this role remote?
Yes. The posting describes the role as 100 percent remote within the United States.
What is the pay and employment type?
The posting lists a salary range of $160,000 to $180,000 per year for a full-time, direct W2 position.
Can the company sponsor work visas?
Candidates holding EAD status, green cards, or U.S. citizenship, along with H-1B transfer candidates, are welcome to apply. The company cannot sponsor new H-1B petitions for this role.
How do I apply?
Send a resume or call (908) 676-4399. The posting does not list an email address or application link.
Sample Interview Questions
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