Principal Data Scientist, Consulting

The Company

Cognizant (NASDAQ:CTSH) is a leading provider of information technology, consulting, and business process outsourcing services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.), Cognizant has over 350,000 employees as of January 2024. Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 1000, and the Fortune 500 and is ranked among the top performing and fastest growing companies in the world.

Cognizant Consulting

At Cognizant, our consultants orchestrate the capabilities to truly change the game across strategy, design, technology and industry/functional knowledge to deliver insight at speed and solutions at scale. Our consulting services elevate the unique abilities and business aspirations of customers and employees and build relationships based on trust and value.

Description:

We are seeking a highly skilled and technically proficient Lead Data Scientist to join our consultancy team. This is a fully remote position requiring a deep technical background in data science, machine learning, and analytics. The ideal candidate will lead client projects, advocate for high-quality standards, and implement cutting-edge data science solutions. Experience with generative AI technologies is highly desirable. You should be comfortable working independently while collaborating with cross-functional teams and communicating complex technical insights to diverse stakeholders.

Roles and Responsibilities:

• Lead the design, development, and deployment of machine learning models and data solutions for clients.
• Act as a champion for high-quality, reproducible data science practices.
• Collaborate with clients to understand business requirements and translate them into actionable data science projects.
• Present insights, reports, and project outcomes to both technical and non-technical stakeholders.
• Oversee the integration of data science solutions with client systems.
• Ensure adherence to best practices in version control, documentation, and code quality.
• Stay updated on emerging data science trends and tools, including generative AI technologies, and apply them where relevant.

Skills:

• Proficiency in machine learning algorithms in domains like NLP, Time Series Forecasting, Recommender Systems and Optimisation
• Solid understanding of statistical analysis, A/B testing, and experiment design.
• Excellent communication skills, both written and verbal, with the ability to explain complex technical concepts to non-technical stakeholders.
• Strong programming skills in Python (including libraries like NumPy, Pandas, scikit-learn, TensorFlow, etc.).
• Experience with generative AI models and tools (e.g., GPT, AWS Bedrock etc.).
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Plotly).
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and deployment of machine learning models.
• Strong attention to detail, with an emphasis on quality and reproducibility.
• Experience with version control systems such as Git.