AI Data Science Associate Director

Found in: Resume Library US A2 - 2 weeks ago


Columbia Maryland, United States Blend360 Full time
Job Description

You will work as part of our global Data Science team to provide data driven AI solutions for our customers using state-of-the-art methods and tools. 

Work with practice leaders and clients to understand business problems, industry context, data sources, potential risks, and constraints 

Work with practice leaders to get stakeholder feedback, get alignment on approaches, deliverables, and roadmaps 

Create and maintain efficient data pipelines, often within clients’ architecture. Typically, data are from a wide variety of sources, internal and external, and manipulated using SQL, spark, and Cloud big data technologies 

Assemble large, complex data sets from client and external sources that meet functional business requirements. 

Build analytics tools to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.  

Perform data cleaning/hygiene, data QC, and integrate data from both client internal and external data sources on Advanced Data Science Platform. Be able to summarize and describe data and data issues  

Utilize deep learning principles and architectures, including CNNs, RNNs, and transformers,  apply these techniques to natural language processing tasks.

Manipulate model parameters to achieve desired outcomes in text generation.

Craft effective prompts that guide AI models to generate desired outputs. Understand how different prompt structures influence AI behavior.

Use RAG models, and combine a retrieval component with a generator to enhance the quality and relevance of the AI's output. Understand how to effectively integrate external knowledge sources into AI responses.

Train and fine-tune models on specific datasets to improve performance and ensure the relevance of the outputs to the task at hand.

Conduct statistical data analysis, including exploratory data analysis, data mining, and document key insights and findings toward decision making 

Document predictive models/machine learning results that can be incorporated into client-deliverable documentation 

Assist client to deploy models and algorithms within their own architecture 



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