AI engineer Proficiency in programming languages such as Python, Java, or R with at least 3 yrs exp. Experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Familiarity with cloud platforms (e.g., AWS, GCP, Azure) for model deployment and scaling. Understanding of financial data structures and databases.
Role & responsibilities Manage calendars, appointments, and meeting schedules for senior management Prepare, proofread, and format reports, presentations, and documents using MS Excel and PowerPoint Handle confidential information with integrity and discretion Organize and coordinate meetings, events, and travel arrangements Assist in preparing MIS reports, tracking project progress, and maintaining action item logs Follow up on internal and external communications and deadlines Maintain digital and physical records in an organized manner Support in drafting official emails, memos, and business correspondence Provide support on ad-hoc tasks and projects as required by the leadership team
Proficiency in T-SQL, SQL Server Management Studio (SSMS), and SQL Profiler. Experience with SQL Server versions 2019 and above. Strong understanding of database design, normalization, and indexing. Experience with SSIS for ETL processes. Familiarity with SSRS for reporting is a plus.
Role & responsibilities Analyze large, complex datasets using statistical tools and AI models to extract trends, patterns, and actionable insights. Use AI-powered tools (e.g., ChatGPT, Google AutoML, Python libraries like Scikit-learn, TensorFlow) for data cleaning, predictive analysis, and automation. Collaborate with cross-functional teams to define KPIs, track performance metrics, and support data-driven business decisions. Build dashboards and reports using tools such as Power BI, Tableau, or Looker, integrating AI-based recommendations where applicable. Design and implement machine learning models to forecast outcomes, customer behavior, or operational efficiency. Automate repetitive data processes using scripts or AI-driven automation platforms. Communicate findings clearly to technical and non-technical stakeholders. Preferred candidate profile Bachelors or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field. Any AI course/certification is must. 3+ years of experience in a data analyst or similar role. Proficiency in SQL, Python, and/or R. Hands-on experience with AI/ML frameworks such as TensorFlow, Scikit-learn, or OpenAI APIs. Familiarity with NLP techniques and tools (e.g., ChatGPT, LLMs, sentiment analysis). Experience with data visualization tools (e.g., Tableau, Power BI). Strong analytical, problem-solving, and communication skills.
Role & responsibilities Define product vision, roadmap, and growth opportunities aligned with business objectives. Own the end-to-end lifecycle of digital products from ideation and design to launch and optimization. Collaborate with engineering, design, marketing, operations, and compliance teams to deliver high-impact products. Conduct market research, customer interviews, and competitive analysis to inform product decisions. Create detailed product requirements, user stories, and functional specifications. Track product performance and customer feedback to identify areas for improvement. Ensure timely and high-quality delivery of features and enhancements. Act as a product evangelist to build awareness and understanding both internally and externally. Ensure regulatory and compliance standards are adhered to in all product initiatives.
Role & responsibilities Define product vision, roadmap, and growth opportunities aligned with business objectives. Own the end-to-end lifecycle of digital products from ideation and design to launch and optimization. Collaborate with engineering, design, marketing, operations, and compliance teams to deliver high-impact products. Conduct market research, customer interviews, and competitive analysis to inform product decisions. Create detailed product requirements, user stories, and functional specifications. Track product performance and customer feedback to identify areas for improvement. Ensure timely and high-quality delivery of features and enhancements. Act as a product evangelist to build awareness and understanding both internally and externally. Ensure regulatory and compliance standards are adhered to in all product initiatives.
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