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Sr. Data Scientist
Career Insights for Natural Language Processing Engineer
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Based on Georgia data
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What they do
A Natural Language Processing Engineer specializes in developing and implementing algorithms and models tailored for understanding, processing, and generating natural language text. They utilize methodologies such as tokenization, parsing, named entity recognition, part-of-speech tagging, and other NLP techniques to perform tasks including text classification, chatbot development, and other applications where the primary input or output is natural language text.
$108,451 / year median in Georgia
Job Description
Sr. Data Scientist Cognizant - 3.8 Alpharetta, GA Job Details Full-time $130,000 - $150,000 a year 6 hours ago Benefits Paid parental leave Employee stock purchase plan Paid holidays Disability insurance Health insurance Dental insurance 401(k) Paid time off Parental leave Vision insurance Life insurance Qualifications AI models Containerization systems Databricks Big data projects Enterprise software Generative models AI platforms (beyond public GPTs) Computational framework Microservices Machine learning cloud services Collaboration with product development teams Machine intelligence Model deployment Distributed systems Developing large-scale AI models Implementing APIs Cloud Native Design Cloud solution engineering Distributed computing Business requirements Machine learning libraries Machine learning frameworks Generative AI Cross-functional communication Full Job Description About the role As a Senior Data Scientist , you will make an impact by designing, developing, and deploying scalable machine learning and generative AI solutions that drive business value and innovation. You will be a valued member of the Data & AI team and work collaboratively with data engineers, machine learning engineers, cloud architects, product teams, and business stakeholders to deliver production-ready AI capabilities. In this role, you will: Design, build, and deploy scalable machine learning and generative AI solutions in cloud-based environments. Develop and optimize predictive models using Python and modern machine learning frameworks. Leverage Google Cloud Platform (GCP), Databricks, and Kubernetes to operate AI and ML workloads. Integrate large language models (LLMs) and generative AI frameworks into enterprise applications and business processes. Establish monitoring, logging, and performance tracking processes to ensure model reliability, scalability, and governance in production environments.
Work model:
We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring 3 days a week in a Cognizant or client office in Alpharetta, GA . Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs. The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations. What you need to have to be considered: Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field. 5+ years of experience developing, deploying, and supporting machine learning or AI solutions in enterprise environments. Strong programming experience with Python and machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. Hands-on experience with Google Cloud Platform (GCP) and Databricks. Experience deploying and managing containerized applications using Kubernetes. Experience working with Generative AI technologies and frameworks, including Hugging Face, LangChain, or LLM APIs. Knowledge of distributed computing and large-scale data processing architectures. Experience building and consuming RESTful APIs and microservices. Strong communication and collaboration skills with the ability to translate business requirements into technical solutions. These will help you stand out: Experience with Vertex AI and other GCP-native machine learning services. Knowledge of MLOps best practices, including CI/CD pipelines and model lifecycle management. Experience implementing model monitoring, observability, and governance frameworks. Experience working with cloud-native data platforms and data engineering workflows. Exposure to responsible AI, prompt engineering, and AI model evaluation methodologies. We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role. Please note, this role is not able to offer visa transfer or sponsorship now or in the future
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Salary and Other Compensation :
Applications will be accepted until September 20, 2026 The annual salary for this position is between $ 130,000 - $ 150,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits:
Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: Medical/Dental/Vision/Life Insurance Paid holidays plus Paid Time Off 401(k) plan and contributions
Long-term/Short-term Disability Paid Parental Leave Employee Stock Purchase Plan Disclaimer:
The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.