We are seeking a skilled Associate Data Scientist with strong expertise in Python, Machine Learning, Deep Learning, Azure, and production-grade AI solutions to design, develop, deploy, and support intelligent services that address complex business problems.
In this role, you will work across the complete AI and machine learning lifecycle, from data exploration, preprocessing, feature engineering, visualisation, and prototyping through model development, microservice implementation, deployment, and production support. You will collaborate with other data scientists, machine learning engineers, software engineers, QA engineers, business users, and analysts to identify opportunities and deliver scalable cognitive and AI-enabled solutions.
Key Responsibilities
Work collaboratively with other data scientists, machine learning engineers, software engineers, QA engineers, business analysts, and other cross-functional stakeholders.
Participate in all phases of the AI and machine learning use-case lifecycle, from initial exploration and prototyping through design, implementation, deployment, and production support.
Perform data collection, data cleansing, preprocessing, transformation, feature engineering, exploratory data analysis, and data visualisation.
Design and implement automated workflows for data collection, validation, preprocessing, and feature generation.
Develop, evaluate, optimise, and maintain machine learning and deep learning models to address business problems.
Develop Python-based applications and services using frameworks such as Flask and relevant API development technologies.
Use scikit-learn, PyTorch, Pandas, and related Python libraries to build efficient data science and machine learning solutions.
Perform systematic debugging, interpret application tracebacks, conduct root-cause analysis, and resolve issues across data, model, API, application, infrastructure, and deployment layers.
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Apply a high-level understanding of Generative AI models, frameworks, capabilities, and limitations to evaluate their suitability for different business problem statements.
Work with Azure Kubernetes Service (AKS) to monitor deployed services, investigate application and infrastructure health, and analyse resource utilisation.
Collaborate on the integration of front-end, back-end, API, data, model, and infrastructure components within end-to-end applications.
Create and maintain technical documentation covering data pipelines, model design, application architecture, APIs, deployment procedures, and production support processes.
Required Qualifications
Strong hands-on expertise in Python, with the ability to investigate documentation and online technical resources to resolve unfamiliar problems independently.
Hands-on experience with Python frameworks and libraries including scikit-learn, Pandas ,Numpy and PyTorch.
Strong understanding of data collection, data preprocessing, feature engineering, exploratory data analysis, statistical analysis, and data visualisation.
Low-level architectural understanding of traditional machine learning models, including their internal behaviour, assumptions, strengths, limitations, and appropriate areas of application.
High-level understanding of Generative AI models, Large Language Models, AI frameworks, and common application patterns.
Ability to evaluate how Generative AI and machine learning technologies can be applied to different business problem statements.
Experience with SQL and relational database technologies such as SQL and MySQL.
Experience supporting production applications, investigating incidents, performing root-cause analysis, and implementing corrective actions.
Preferred Qualifications
Previous professional experience(atleast 1 year ) or education focused on statistics, data science, machine learning, artificial intelligence, computer science, or a related discipline.
Experience with cloud-based data processing platforms preferably in Azure
Experience developing and deploying containerised machine learning services or cognitive microservices on Azure.
Knowledge of REST APIs, API design principles, microservices architecture, and distributed application patterns.
Familiarity with model monitoring, model performance analysis, data quality validation, and production machine learning operations.
Understanding of Generative AI concepts such as prompt engineering, embeddings, vector search, retrieval-augmented generation, model orchestration, and responsible AI considerations.
Experience automating machine learning, data-processing, testing, deployment, or operational support workflows.
Working knowledge of DevOps and MLOps practices, including source control, automated build and release pipelines, model deployment, monitoring, and operational support.
Experience translating business requirements into analytical, machine learning, cognitive, or Generative AI solutions.
Ability to explain model outputs, technical limitations, architectural decisions, and operational risks to business and technical stakeholders.
Why Join Us?
This is an opportunity to work across the complete lifecycle of enterprise AI solutions, from identifying high-value business opportunities and exploring data through model development, cognitive microservice implementation, cloud deployment, and production support. You will collaborate with multidisciplinary teams, apply machine learning, deep learning, and Generative AI technologies to real-world problems, and contribute to the delivery of scalable, reliable, and business-focused intelligent solutions.
About State Street
Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.
We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.
As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.
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