Senior Data Scientist

Bright Vision Technologies

. Design, develop, deploy, and optimize enterprise-grade data science and machine learning solutions .

Posted 11/4/2026full-timeRemote • United StatesSenior💰 $160,000 - $180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying enterprise-grade machine learning solutions, with a strong foundation in statistics, data modeling, and predictive analytics. Proficient in utilizing modern data science libraries and cloud technologies to drive data-driven decision-making and support strategic business outcomes.

Highest-signal resume keywords

Machine Learning Model DevelopmentPredictive Analytics SolutionsPython ProgrammingSQL ProficiencyCloud Deployment (AWS, Azure, GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning AlgorithmsData StructuresFeature EngineeringModel Evaluation TechniquesData VisualizationETL DevelopmentStatistical AnalysisPredictive ModelingData ExplorationDebugging

Soft Skills

Analytical ThinkingProblem-SolvingCommunication Skills

Tools & Technologies

Scikit-learnTensorFlowPyTorchPandasNumPySparkHadoopSnowflakeDatabricksGit

Industry Keywords

Data ScienceMachine LearningAgile EnvironmentMLOpsReal-Time Machine LearningData GovernanceContinuous Machine LearningRecommendation SystemsNatural Language ProcessingDeep Learning

Tech Stack

Tools & technologies

AirflowAWSAzureBigQueryCloudDockerETLGoogle Cloud PlatformHadoopKafkaKubernetesNoSQLNumpyPandasPythonPyTorchScikit-LearnSnowflakeSparkSQLTensorflow

About the role

Key responsibilities & impact

Design, develop, deploy, and optimize enterprise-grade data science and machine learning solutions
Translate business problems into analytical solutions
Develop predictive models and deploy machine learning pipelines
Monitor model performance and support data-driven decision-making throughout the operational lifecycle
Work with large-scale structured and unstructured datasets using modern analytics platforms and cloud technologies
Collaborate with business stakeholders, data engineers, software developers, product managers, and cross-functional teams in an Agile environment
Deliver scalable, accurate, and impactful data science solutions supporting strategic business outcomes

Requirements

What you’ll need

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a closely related quantitative discipline
6+ years of experience stated for the position
Five or more years of professional experience developing production-grade machine learning models, predictive analytics solutions, and enterprise data science applications
Strong 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, TensorFlow, PyTorch, Pandas, NumPy, and modern data science libraries
Production-level experience designing, training, validating, deploying, and monitoring machine learning models
Experience with regression, classification, clustering, forecasting, recommendation systems, and natural language processing applications
Experience with relational and NoSQL databases, large-scale datasets, data warehouses, and distributed data processing platforms such as Spark, Hadoop, Snowflake, Databricks, or BigQuery
Strong SQL skills and experience with data exploration, feature engineering, query optimization, ETL development, data visualization, and business intelligence reporting
Experience with Git-based version control, CI/CD, MLOps, model deployment pipelines, code review, and collaborative software development methodologies
Experience deploying machine learning solutions on AWS, Azure, or GCP, including managed AI/ML services, storage, networking, and identity management
Strong debugging, analytical thinking, problem-solving, root-cause analysis, and ability to communicate findings and business recommendations
U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply
Unable to sponsor new H-1B visa petitions
Preferred: experience with real-time machine learning systems, recommendation engines, streaming analytics, event-driven architectures, Kafka, Spark Streaming, Docker, Kubernetes, Kubeflow, MLflow, Airflow, deep learning, reinforcement learning, computer vision, generative AI, LLMs, XAI, model fairness, responsible AI, automated testing, model monitoring, feature stores, experiment tracking, data governance, and continuous machine learning delivery pipelines

Benefits

Comp & perks

Comprehensive benefits
Competitive compensation package
Supportive work-life balance
Career growth potential
Continuous learning and growth opportunities