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Data Scientist – Financial Services

SymphonyAI -
Bengaluru, Karnataka

Apply Now

Job details

Full-time
₹21,96,882 a year
11 hours ago

Qualifications

CI/CD
Oracle
Law
Doctoral degree
Computer Science
AIX
DB2
Spark
NumPy
UNIX
Microsoft SQL Server
Solaris
Master's degree
Databases
SQL
Pandas
Bachelor's degree
Machine learning
PostgreSQL
Continuous integration
User acceptance testing
Natural language processing
UX
Software development
Product demos
APIs
Agile
Financial services
Fraud prevention and detection
Linux
Data science
AI
Leadership
Communication skills
Banking
Python
SDLC

Full job description

Introduction:

We are seeking a client-facing Data Science Consultant with AI/ML expertise to design, build, and deploy data science solutions for financial services customers. You will translate complex business challenges into AI use cases, develop and operationalize models (including LLM/NLP, graph, supervised and unsupervised learning), and integrate them with SymphonyAI products and customer ecosystems. You will lead discovery, deliver PoCs and pilots, establish robust MLOps and model governance, and ensure successful adoption and outcomes.

Job Description:

Key Responsibilities

Client engagement and solution design

Lead discovery workshops to elicit requirements, define success metrics, and translate business problems into AI solutions and delivery plans.
Provide innovation, leadership and influence in the design of client-centric solutions that are aligned with the SymphonyAI’s product offering.
Create SOW inputs, estimates, and technical approach for services engagements; support pre-sales with demos, POVs, and solution narratives.
Manage the client review and sign-off process for the suite of functional documents and artefacts.
Take overall responsibility for the documentation of functional artefacts.

Model development and delivery

Build and evaluate models for key financial services use cases (e.g., anti-money laundering, fraud detection, alert triage, trading surveillance, credit risk, customer intelligence).
Apply advanced techniques: NLP/LLMs (RAG, summarisation, extraction, classification), graph/network analytics, time series, anomaly detection, and ensemble methods.
Implement explainability (e.g., SHAP, LIME), bias/fairness testing, performance monitoring, and model risk controls to meet regulatory and enterprise standards.
Deliver high-quality PoCs and pilots; productionise with engineering using robust MLOps practices (CI/CD, model registry, experiment tracking, feature management).

Data engineering and integration

Work with client and internal teams to profile, transform, and validate data; build performant pipelines using SQL/Spark and orchestration tools.
Integrate AI services with SymphonyAI products and client systems via APIs, microservices, and event streams; optimize for scalability, latency, and cost.
Implement retrieval components (e.g., vector databases) and prompt orchestration frameworks for LLM-based solutions.

Change management and enablement

Plan and execute user acceptance testing, training, and knowledge transfer to drive adoption and embed AI in business workflows.
Mentor customer and internal teams; contribute reusable assets (templates, prompts, pipelines, notebooks) to accelerate future engagements.
Provide thought leadership by sharing best practices and feedback to product and R&D for roadmap influence.

Key Requirements

Expertise in industry standard modelling tools and methods
Client-facing experience is essential including delivering presentations and product demonstrations, running workshops and managing client's expectations.
Experience of delivering complex business or technology solutions, from gathering requirements to designing solutions
Excellent communication skills, both written and verbal and able to communicate confidently and effectively at any level of the organisation.
Ability to grasp technical concepts and translate them into business solutions.
Good working knowledge of SQL and experience with Databases such as Oracle, DB2, SQL Server and Postgres
Good working knowledge of Python (Pandas, NumPy, and scikit-learn) or similar.
An understanding of compliance processes and workflows within the financial services industry advantageous
Experience of software development lifecycle practices (preferably Agile).
Good knowledge of IT systems, architectures and terminology.
Strong interpersonal/leadership skills.
Knowledge and exposure with Unix (Solaris, AIX, Linux, HP UX) is advantageous
Advantageous to have knowledge of financial regulatory modules, ideally to include AML, KYC, FATCA, CRS, and related topics.

About Us:

Qualifications

Education: Bachelor’s degree in a quantitative field (Computer Science, Statistics, Mathematics, Engineering) required; Master’s or PhD preferred.
Experience: 5–10 years in data science/ML with at least 3 years in financial services domains (banking, payments, insurance, capital markets) and 2+ years in client-facing or professional services roles.

Apply Now

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