Applied Data Scientist

As an Applied Data Scientist , you will make an impact by designing, developing, and implementing AI and machine learning solutions that solve complex business challenges and drive measurable outcomes. You will be a valued member of the AI and Data Science team and work collaboratively with business stakeholders, data engineers, architects, and technology teams to deliver scalable, production-ready solutions.

In this role, you will:

• Collaborate with business stakeholders to understand challenges, define requirements, and identify opportunities for AI and machine learning solutions.
• Perform exploratory data analysis, statistical modeling, feature engineering, and machine learning experimentation to generate business insights.
• Design, develop, test, and deploy machine learning models that address business needs and support decision-making.
• Research, evaluate, and prototype emerging AI technologies, including generative AI, large language models, and advanced machine learning techniques.
• Partner with cross-functional teams to integrate, monitor, optimize, and maintain machine learning solutions in production environments.

Work model

At Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various wellbeing programs. Based on this role’s business requirements, this is an onsite position requiring 5 days per week in a client or Cognizant office in Mason, Ohio .

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.

• Proven experience as a Data Scientist, Applied Data Scientist, or Machine Learning Engineer delivering business-focused solutions.
• Strong proficiency in Python or R and experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Solid understanding of statistical analysis, predictive modeling, machine learning algorithms, and data mining techniques.
• Experience developing, deploying, and supporting machine learning solutions in production environments.
• Ability to translate business problems into actionable data science solutions while effectively communicating technical concepts to diverse stakeholders.

These will help you stand out

• Experience with generative AI, large language models (LLMs), deep learning, and emerging AI technologies.
• Familiarity with Azure, Databricks, Spark, Synapse, and Lakehouse architectures.
• Experience deploying machine learning solutions using cloud-native services, Docker, or Kubernetes.
• Knowledge of MLOps practices, model monitoring, performance optimization, and retraining strategies.
• Experience working in Agile, cross-functional delivery environments and presenting analytical findings to non-technical audiences.

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.

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.