Technogen Inc.
Data Scientist
Camden, New Jersey, USA · contract, third party
Sponsorship not specifiedDetected 65 days ago
PythonAlgorithmsSQLNoSQLAWSGCPAzureCloud PlatformsDockerKubernetesDevOpsKafkaMachine LearningDeep LearningTensorFlowPyTorchscikit-learnSparkData EngineeringData ScienceData VisualizationNLPComputer VisionMLOps
About the role
- TECHNOGEN, Inc. is a Proven Leader in providing full IT Services, Software Development and Solutions for 15 years.
- TECHNOGEN is a Small & Woman Owned Minority Business with GSA Advantage Certification.
- We have offices in VA; MD & Offshore development centers in India.
Responsibilities
- Acquire access to various databases and source systems (SQL, NoSQL, graph databases) and create data pipelines for efficient and repeatable data science projects.
- Perform feature selection and engineering, create predictive variables, and experiment with transformations to enhance performance and interpretability.
- Collaborate with MLOps, data engineers, and IT to evaluate deployment options, and establish best practices around ML production infrastructure.
- Create dashboards, and interactive visualizations that communicate results to a wide range of audiences, turning technical findings into actionable recommendations.
- This role involves analyzing large datasets, developing AI /ML /optimization models, and translating findings into actionable insights.
- The Data Scientist partners with business and operational leaders, supports senior leadership with analytics, and fosters a culture of data-driven decision-making across the organization.
Nice to have
- Specialization in ML, AI, cognitive science, or data science is highly preferred.
Benefits
- Long-Term About the Role The Data Scientist plays a pivotal role in planning, executing, and delivering machine learning-based projects that drive business impact.
- Design, develop, and validate machine learning, statistical, and optimization models for classification, regression, clustering, recommendation, and prediction tasks.
- Continuously monitor execution and health of production ML models, recalibrating as needed and updating them to reflect new data or changing business conditions.
- Qualifications Education Master's, or PhD in Computer Science, Data Science, Engineering, Statistics, Applied Mathematics, Operations Research, or a related quantitative field.
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