Hiring: W2 Candidates Only
Visa: Open to any visa type with valid work authorization in the USA
Summary
A Data Scientist is responsible for developing advanced analytical models and applying machine learning techniques to extract insights from complex and large-scale datasets. This role supports strategic decision-making, predictive analytics initiatives, and data-driven business transformation across the organization.
Key Responsibilities
Design, develop, and deploy predictive models and machine learning algorithms to solve business problems.
Analyze large and complex datasets to identify trends, patterns, correlations, and actionable insights.
Collaborate with business stakeholders, analysts, and product teams to understand data needs and define analytical objectives.
Build data pipelines and feature engineering processes to support model development and deployment.
Create data visualizations, dashboards, and analytical reports to communicate insights to technical and non-technical audiences.
Optimize data collection, storage, and retrieval processes to improve performance and scalability.
Ensure model accuracy, reproducibility, scalability, and compliance with data governance standards.
Conduct A/B testing, experimentation, and hypothesis testing to validate business strategies and product enhancements.
Monitor model performance in production and continuously refine algorithms based on feedback and new data.
Document models, assumptions, methodologies, and data sources for transparency and auditability.
Evaluate emerging tools, frameworks, and algorithms to improve analytical capabilities.
Work closely with data engineers to integrate models into enterprise data platforms.
Provide guidance on data science best practices and promote a data-driven culture across teams.
Mentor junior data scientists, analysts, and engineers to build technical excellence within the organization.
Qualifications
Bachelor s or Master s degree in Data Science, Computer Science, Statistics, or a related field.
3-6 years of hands-on experience in data science, advanced analytics, or machine learning.
Proficiency in Python, R, SQL, and popular machine learning libraries and frameworks.
Strong foundation in statistics, probability, and applied mathematics.
Demonstrated ability to translate complex data into business-relevant insights.
Preferred Skills / Duties
Experience working with cloud-based data platforms such as AWS, Google Cloud Platform (Google Cloud Platform), or Microsoft Azure.
Knowledge of deep learning, natural language processing (NLP), and artificial intelligence (AI) frameworks.
Familiarity with big data technologies, distributed computing, and data engineering pipelines.
Excellent data storytelling, visualization, and presentation abilities.
Strong communication, problem-solving, and stakeholder collaboration skills.
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