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Data Science Architect (FinTech, Insurance, Capital Market)
Company: Qubist Solutions LLC
Job Location: Bengaluru, Karnataka, India
Employment Type: Full-time
Experience Required: 8+ years
Were Hiring: Data Science Architect (FinTech / Private Credit)
Are you an experienced Data Architect with deep capital markets expertise looking to build cutting-edge data platforms powered by modern LLMs and cloud technologies Join our team to drive end-to-end data architecture and analytics for our buy-side platform!
Location: Bangalore / Hybrid]
Employment Type: Full-time
Experience Level: Senior (8+ years)
About the Role
As a Data Science Architect, you will lead the evolution of our enterprise data warehouse, integrate AI/LLM technologies, and connect key trading, portfolio management, and accounting platforms. Youll work closely with portfolio managers, traders, and finance teams to deliver high-impact data solutions and real-time reporting.
Key Responsibilities
Data Architecture & AI: Design enterprise data warehouses incorporating LLMs, machine learning automation, and unstructured data.
System Integration: Lead integrations with OMS, PMS, and IBOR systems using Python, T-SQL, and RESTful APIs.
Analytics & Reporting: Build executive dashboards and ad-hoc reporting tools for front and middle-office stakeholders.
Operations & Stability: Provide L2 support, automate routine operational tasks, and ensure maximum stability for mission-critical pipelines.
What Were Looking For
10+ years of hands-on experience in enterprise financial technology (buy-side / private credit preferred).
Advanced T-SQL skills (stored procedures, query performance tuning) and strong Python programming.
Deep experience with cloud data platforms (Snowflake, Databricks, Redshift, or Azure Synapse).
Familiarity with capital markets systems (Aladdin, Allvue, Bloomberg, Refinitiv).
Experience or strong interest in configuring and deploying LLM & AI/ML technologies into enterprise pipelines.
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field.
How to Apply
Interested in taking our data infrastructure to the next level Apply directly through LinkedIn or send your resume to hidden_email
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Warehouse .
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