Data Science Engineer

SEEKING DATA ARCHITECTFULL-TIME 40 HRS/WK, ON-SITE IN WASHINGTON DC

As a Data Science Engineer, you will play a critical role in leveraging data-driven insights to drive informed decision-making and enhance business processes on the Azure cloud platform. Your expertise in data analysis, machine learning, software engineering, and Azure technologies will be instrumental in developing scalable data solutions, building predictive models, and implementing data-driven applications. You will collaborate closely with cross-functional teams to extract, transform, and analyze complex datasets using Azure services to provide valuable business insights.

• Collaborate with stakeholders to understand business objectives and identify opportunities for leveraging data-driven solutions on the Azure cloud platform.
• Extract, clean, transform, and analyze large and complex datasets using Azure Data Services, such as Azure Data Lake Storage, Azure Databricks, or Azure SQL Database, to generate actionable insights and drive informed decision-making.
• Develop and implement machine learning models and algorithms using Azure Machine Learning services, Azure Databricks, or other relevant Azure technologies for predictive analytics, pattern recognition, and optimization.
• Apply statistical techniques to analyze data, identify trends, and perform hypothesis testing to validate models and findings.
• Design and implement scalable data pipelines, ETL processes, and data workflows on Azure, leveraging technologies like Azure Data Factory, to efficiently process, transform, and store large volumes of data.
• Collaborate with software engineers to deploy and integrate data-driven applications and systems into Azure cloud environments.
• Continuously monitor and evaluate model performance, making improvements and optimizations using Azure Machine Learning pipelines or other relevant tools.
• Stay up-to-date with emerging trends and advancements in data science, machine learning, software engineering, and Azure technologies, recommending innovative solutions and best practices for Azure data solutions.
• Effectively communicate complex findings and insights to non-technical stakeholders, enabling data-driven decision-making across the organization.

Education:

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

Experience:

• Minimum of 5 years of experience as a Data Science Engineer or a similar role.
• Strong proficiency in data analysis, statistical modeling, and machine learning techniques.
• Proven experience in applying machine learning algorithms and frameworks to real-world problems.
• Proficiency in programming languages commonly used in data science, such as Python or R.
• Experience with data visualization tools and libraries, such as Power BI, Matplotlib, or ggplot.
• Solid understanding of software engineering principles and best practices.
• Familiarity with data manipulation and querying languages, such as SQL.
• Experience in developing and deploying data-driven applications in production environments.
• Strong problem-solving skills and the ability to handle complex data challenges.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.

Technology

Skills:

• Proficiency in programming languages commonly used in data science, such as Python or R.
• Experience with data analysis and manipulation libraries and frameworks, such as pandas, Num Py, or dplyr.
• Knowledge of machine learning frameworks and libraries, such as scikit-learn, Tensor Flow, or PyTorch.
• Familiarity with data visualization tools and libraries, such as Power BI, Matplotlib, or ggplot.
• Understanding of database concepts and proficiency in SQL for data manipulation and querying.
• Experience with big data technologies, such as Apache Hadoop, Spark, or distributed computing frameworks.
• Proficiency in utilizing Azure Data Services, such as Azure Data Lake Storage, Azure Synapse Analytics, or Azure SQL Database, for data processing and storage on the Azure cloud platform.
• Experience with Azure Machine Learning services for building and deploying machine learning models.
• Proficiency in utilizing Azure Databricks for collaborative analytics, machine learning workflows, and big data processing on Azure.
• Knowledge of software engineering principles and practices, including version control (e.g., Git) and agile development methodologies.
• Familiarity with Azure cloud platform and services, such as Azure Data Factory, Azure Dev Ops, or Azure Functions.
• Understanding of data security and privacy considerations in data science projects on the Azure cloud platform.

If you are interested, please send your resume to