Data Scientist Senior Consulting Manager at Cognizant

Lead Data Scientist, AI/ML

About Cognizant Consulting

Cognizant Consulting is a global community of experts dedicated to helping clients reimagine their business - blending deep industry and technology advisory capability to create innovative solutions for Fortune 500 clients. And now, we’re looking for our next colleague who’ll join us in shaping the future of business. Could it be you?

About the role

As a Lead Data Scientist, AI/ML, you will design, build, and operationalise modern analytics solutions that drive measurable value. You will also take on leadership responsibilities—guiding small, high performing teams as they deliver impactful AI initiatives. You’ll work closely with business stakeholders, product owners, architects, and cross-functional delivery teams to embed AI/ML into digital products and services, ensuring that complex technical insights translate into clear, compelling business outcomes.

In this role, you will

· Apply advanced statistical and scientific methods (e.g., hypothesis testing, inference) to frame problems, validate assumptions, and quantify impact.

· Engineer and integrate data across structured and unstructured sources; oversee data wrangling and feature engineering for production grade pipelines.

· Build and guide development of models using Python and libraries such as scikit learn, pandas, numpy, and develop deep learning solutions using TensorFlow and PyTorch.

· Process big data at scale using Spark and cloud native tools (e.g., AWS Glue, Azure Data Factory).

· Operationalise ML solutions using MLOps practices—CI/CD for models, reproducible training, and automated deployment.

· Deliver applied ML and AI across predictive analytics, time series forecasting, anomaly detection, NLP, computer vision, and Generative AI (e.g., retrieval systems, chatbots).

· Govern and monitor models in cloud environments; establish retraining schedules, performance monitoring, and risk controls.

· Design machine learning architectures that support pre sales engagements and accelerate the successful initiation of new projects.

· Lead agile delivery practices (Scrum/SAFe) using tools such as JIRA and Trello; ensure backlog health and delivery quality.

· Coach, mentor, and develop team members; advocate for data driven decision making across the organisation.

· Think strategically about data collection, metric design, and ethical AI—driving responsible and transparent use of data.

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 2-3 days a week in a client or Cognizant office in London, UK. Regardless of your working arrangement, we are here to support a healthy work-life balance though 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 must have to be considered

• 5+ years of hands‑on experience in statistical methods and ML engineering across the end‑to‑end lifecycle (data prep → modelling → deployment → monitoring).
• Proficiency in Python and strong command of ML/DS libraries (scikit‑learn, pandas, numpy, TensorFlow/PyTorch).
• Experience working with GCP, AWS and Azure data services.
• Demonstrated MLOps expertise (CI/CD, model registries, reproducible training, automated deployment).
• Ability to communicate technical insights clearly to non‑technical audiences; strong storytelling with data.
• Proven agile delivery experience; confident in facilitating ceremonies and partnering with product owners.
• Strong grounding in data security and compliance, especially in regulated industries (e.g., BFSI, healthcare, life sciences).
• Working knowledge of cloud‑native software architecture, service design/design thinking, and version control (Git).
• Experience leading small AI teams and mentoring junior data scientists on AI/ML initiatives.

These will help you succeed (nice‑to‑haves)

• Experience designing gen-AI and agentic AI architectures (e.g., using Google's ADK or similar frameworks).
• Background in real‑time analytics and event‑driven architectures.
• Prior consulting experience (client‑facing, pre‑sales, solutioning) and domain expertise.
• A strong track record of driving innovation and accelerating the adoption of advanced analytics in complex organisations.

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.