Position: Data Scientist
Location: NY/NJ (Only Locals) Onsite
Duration: Contract
Key Responsibilities:
Lead the development and implementation of data science projects using Azure and AWS. Exposure to Gen AI is a must with experience in doing PoC/Pilot projects
Engage in customer discussions to understand their requirements and provide technical solutions.
Collaborate with the offshore team to ensure seamless project execution and delivery.
Design and deploy scalable data pipelines and machine learning models on cloud platforms.
Provide technical guidance and mentorship to junior data scientists and engineers.
Conduct data analysis, visualization, and reporting to derive actionable insights.
Ensure data quality, integrity, and security throughout the project lifecycle.
Stay updated with the latest advancements in data science and cloud technologies.
Utilize Azure Open AI GPT-4 for developing advanced natural language processing solutions.
Required Skills and Qualifications:
10+ years of experience in data science, with a focus on Azure and AWS.
Proven expertise in customer discussions and translating business requirements into technical solutions.
Strong technical skills in data engineering, machine learning, and cloud computing.
Proficiency in programming languages such as Python, R, and SQL.
Experience with data visualization tools like Power BI, Tableau, or similar.
Experience with Azure OpenAI GPT-4 for natural language processing tasks.
Preferred Qualifications:
Experience in managing and leading data science teams.
Certifications in Azure and AWS cloud platforms.
Knowledge of big data technologies like Hadoop, Spark, and Kafka.
Familiarity with DevOps practices and tools for continuous integration and deployment.
We are looking for an experienced Senior Data Scientist with a strong background in Azure and AWS. The ideal candidate will have extensive experience in customer discussions and technical expertise to drive project activities forward. This role requires a deep understanding of Data landscape, data science, cloud technologies, and excellent client facing skills with an ability to communicate technical details to Business users effectively.
Key Responsibilities:
Lead the development and implementation of data science projects using Azure and AWS. Exposure to Gen AI is a must with experience in doing PoC/Pilot projects
Engage in customer discussions to understand their requirements and provide technical solutions.
Collaborate with the offshore team to ensure seamless project execution and delivery.
Design and deploy scalable data pipelines and machine learning models on cloud platforms.
Provide technical guidance and mentorship to junior data scientists and engineers.
Conduct data analysis, visualization, and reporting to derive actionable insights.
Ensure data quality, integrity, and security throughout the project lifecycle.
Stay updated with the latest advancements in data science and cloud technologies.
Utilize Azure Open AI GPT-4 for developing advanced natural language processing solutions.
Required Skills and Qualifications:
10+ years of experience in data science, with a focus on Azure and AWS.
Proven expertise in customer discussions and translating business requirements into technical solutions.
Strong technical skills in data engineering, machine learning, and cloud computing.
Proficiency in programming languages such as Python, R, and SQL.
Experience with data visualization tools like Power BI, Tableau, or similar.
Experience with Azure OpenAI GPT-4 for natural language processing tasks.
Preferred Qualifications:
Experience in managing and leading data science teams.
Certifications in Azure and AWS cloud platforms.
Knowledge of big data technologies like Hadoop, Spark, and Kafka.
Familiarity with DevOps practices and tools for continuous integration and deployment.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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