Who you are: A senior Data Scientist specializing in Advanced Analytics, with expertise in machine learning (ML), predictive modeling, and statistical analysis. Sound experience in leveraging Big-data technologies, AI, and automation to solve complex business problems and enhance decision-making.
Have experience working with Cloudera Data Platform, Apache Spark, Kafka, and Iceberg tables, and you understand how to design and deploy scalable AI/ML models. Your role will be instrumental in data modernization efforts, applying AI-driven insights to enhance efficiency, optimize operations, and mitigate risks.What you’ll do: As a Data Scientist – Advanced Analytics, your responsibilities include:
AI & Machine Learning Model Development
• Developing AI/ML models for predictive analytics, fraud detection, and customer segmentation.
• Implementing time-series forecasting, anomaly detection, and optimization models.
• Working with deep learning (DL) and Natural Language Processing (NLP) for AI-driven automation.
Big Data & Scalable AI Pipelines
• Processing and analyzing large datasets using Apache Spark, PySpark, and Iceberg tables.
• Deploying real-time models and streaming analytics with Kafka.
• Supporting AI model training and deployment on Cloudera Machine Learning (CML).
Advanced Analytics & Business Impact
• Performing exploratory data analysis (EDA) and statistical modelling.
• Delivering AI-driven insights to improve business decision-making.
• Supporting data quality and governance initiatives using Talend DQ.
Data Governance & Security
• Ensuring AI models comply with Bank’s data governance and security policies.
• Implementing AI-driven anomaly detection and metadata management.
• Utilizing Thales CipherTrust for data encryption and compliance.
Collaboration & Thought Leadership
• Working closely with data engineers, analysts, and business teams to integrate AI-driven solutions.
• Presenting AI insights and recommendations to stakeholders and leadership teams.
• Contributing to the development of best practices for AI and analytics.
3-7 years of experience in AI, ML, and Advanced Analytics.
• Proficiency in Python, R, SQL, and ML frameworks (Scikit-learn, TensorFlow, PyTorch).
• Hands-on experience with Big-data technologies (Cloudera, Apache Spark, Kafka, Iceberg table format).
• Strong knowledge of statistical modelling, optimization, and feature engineering.
• Understanding of MLOps practices and AI model deployment.
Develop and implement advanced analytics models, including predictive, prescriptive, and diagnostic analytics to solve business challenges and optimize decision-making processes. Utilize tools and technologies to work with Large and complex datasets to derive analytical solutions.
• Build and deploy machine learning models (supervised and unsupervised), statistical models, and data-driven algorithms for forecasting, segmentation, classification, and anomaly detection.
• Should have strong hands-on experience in Python, Spark and cloud computing.
• Should be independently working and be able to deploy deep learning models using various architectures.
• Should be able to perform exploratory data analysis (EDA) to uncover trends, relationships, and outliers in large, complex datasets. Design and create features that improve model accuracy and business relevance.
• Should create insightful visualizations and dashboards that communicate findings to stakeholders. Effectively translate complex data insights into clear and actionable recommendations.
• Work closely with business leaders, engineers, and analysts to understand business requirements and translate them into analytical solutions that address strategic goals.
• Exposure to Graph AI using DGraph Enterprise.
• Knowledge of cloud-based AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
