Data Entry Question and Answer

~~$150~~ $49

Buy Now

Remote Question and Answer

~~$150~~ $49

Buy Now

Virtual Assistant Question and Answer

~~$150~~ $49

Buy Now

Content Moderator Question and Answer

~~$150~~ $49

Buy Now

Customer Service Question and Answer

~~$150~~ $49

Buy Now

Video Game Tester Question and Answer

~~$150~~ $49

Buy Now

Sr Staff Data Scientist id-7348

April 24, 2025

Job Description Summary

As a Sr Staff Data Scientist, you will lead and work within teams as a technical domain expert addressing statistical, machine learning, and artificial intelligence problems in a commercial technology and consultancy development environment. You will be part of a data science or cross-disciplinary team driving AI business solutions involving large, complex data sets. Potential application areas include time series forecasting, machine learning regression and classification, root cause analysis (RCA), simulation and optimization, large language models, and computer vision. The ideal candidate will be responsible for developing and deploying machine learning models in production environments. This role requires a strong technical background, excellent problem-solving skills, and the ability to work collaboratively with data engineers, analysts, and other stakeholders.

Other Jobs You May Be Interested In

Job Description

Roles and Responsibilities:

Understand business problems and identify opportunities to implement data science solutions.
Develop, verify, and validate analytics to address customer needs and opportunities.
Design, develop, and deploy machine learning models and algorithms
Work in technical teams on the development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
Develop and maintain pipelines for Retrieval-Augmented Generation (RAG) and Large Language Models (LLM).
Collaborate with data scientists to optimize RAG and LLM pipelines for performance and accuracy.
Utilize semantic and ontology technologies to enhance data integration and retrieval. Ensure data is semantically enriched to support advanced analytics and machine learning models.
Interact with cloud services and develop and deploy models within cloud environments such as AWS, Azure, Google Cloud, and Databricks
Perform exploratory and targeted data analyses using descriptive statistics and other methods.
Work with data engineers on data quality assessment, data cleansing, data analytics, and model productionization
Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
Communicate methods, findings, and hypotheses with stakeholders.
Mentor colleagues in technical areas and drive standardization across the analytics enterprise
Review data science/AI projects for technical rigor

Minimum Qualifications:

Bachelor’s degree from accredited university or college with minimum of 6 years of professional experience OR associates degree with minimum of 8 years of professional experience
4 years proficiency in Python (mandatory)
3 years demonstrated expertise in cloud platforms (e.g. AWS, Azure, Google Cloud, Databricks) and their machine learning services
3 years demonstrated expertise working and leading in team settings in various roles
Note: Military experience is equivalent to professional experience

Eligibility Requirement:

Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job.

Desired Characteristics:

Demonstrated skill in defining and delivering customer value.
Demonstrated expertise communicating complex information to executive stakeholders
Demonstrated expertise in critical thinking and problem-solving methods
Demonstrated experience deploying and managing CI/CD pipelines
Demonstrated skill in data management methods and analytic scaling
Demonstrated skill in prescriptive analytics and analytic prototyping.
Demonstrated skill in solutions integration
Demonstrated skill in serving as a change agent.
Demonstrated skill in working in ambiguous environments.