Senior Manager - Technology CIBG-Nitro WS Squad-AA Mashreq Corporate & Investment Banking Group

5.0 - 9.0 years

0 Lacs

karnataka

On-site

Role Overview: The Data & Analytics team at the leading financial institution in MENA is responsible for integrating new data sources, creating data models, developing data dictionaries, and building machine learning models for Wholesale Bank. The primary objective is to design and deliver data products that assist squads at Wholesale Bank in achieving business outcomes and generating valuable business insights. Within this job family, there are two roles - Data Analysts and Data Scientists. Both roles involve working with data, writing queries, collaborating with engineering teams to source relevant data, performing data munging, and extracting meaningful insights from the data. Data Analysts typically work with structured SQL databases or other BI tools and packages, while Data Scientists are expected to develop statistical models and be hands-on with machine learning and advanced programming, including Generative AI. Key Responsibilities: - Extract and analyze data from company databases to optimize and enhance product development and marketing strategies. - Analyze large datasets to uncover trends, patterns, and insights influencing business decisions. - Utilize predictive and AI/ML modeling techniques to enhance customer experience, boost revenue generation, improve ad targeting, and more. - Design, implement, and optimize machine learning models for various applications such as predictive analytics, natural language processing, and recommendation systems. - Stay updated with the latest advancements in data science, machine learning, and artificial intelligence to bring innovative solutions to the team. - Communicate complex findings and model results effectively to both technical and non-technical stakeholders. - Implement advanced data augmentation, feature extraction, and data transformation techniques for optimizing the training process. - Deploy generative AI models into production environments ensuring scalability, efficiency, and reliability for real-time applications. - Use cloud platforms and containerization tools for model deployment and scaling. - Create interactive data applications using Streamlit for various stakeholders. - Conduct prompt engineering to optimize AI model performance and accuracy. - Continuously monitor, evaluate, and refine models to ensure performance and accuracy. - Conduct in-depth research on the latest advancements in generative AI techniques and apply them to real-world business problems. Qualification Required: - Bachelors, Masters or Ph.D in Engineering, Data Science, Mathematics, Statistics, or a related field. - 5+ years of experience in Advanced Analytics, Machine learning, Deep learning. - Proficiency in programming languages such as Python, and familiarity with machine learning libraries. - Experience with generative models such as GANs, VAEs, and transformer-based models. - Strong experience with data wrangling, cleaning, and transforming raw data. - Hands-on experience in developing, training, and deploying machine learning models. - Experience with cloud platforms for model deployment and scalability. - Proficiency in data processing and manipulation techniques. - Hands-on experience in building data applications using Streamlit or similar tools. - Advanced knowledge in prompt engineering, chain of thought processes, and AI agents. - Strong problem-solving skills and effective communication abilities to convey technical concepts. (Note: Any additional details of the company were not provided in the job description.),

Posted 22 hours ago

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