Cognizant, a global community of experts dedicated to helping clients reimagine their business, is seeking a Lead Data Scientist, AI/ML. In this role, you will be responsible for designing, building, and operationalizing modern analytics solutions. You will lead small teams, work with stakeholders to embed AI/ML into digital products, and ensure technical insights translate into business outcomes.
What You'll Do
- 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).
- Operationalize 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.
What We're Looking For
- 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.
Nice to Have
- 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.
Technical Stack
- Languages & Core ML: Python, scikit-learn, pandas, numpy, TensorFlow, PyTorch
- Big Data & Cloud: Spark, AWS Glue, Azure Data Factory, GCP, AWS, Azure
- Tools: Git, JIRA, Trello
Team & Environment
You will lead small, high-performing teams.
Work Mode
This is a hybrid position based in London, UK.
Cognizant is an equal opportunity employer.
