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Sympera AI

AI-powered platform for relationship banking

Data Science Consultant

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • Expertise in industry-standard modelling tools and methods.
  • Client-facing experience delivering presentations and product demonstrations, running workshops, and managing client expectations.
  • Experience delivering complex business or technology solutions, from gathering requirements to designing solutions.
  • Excellent written and verbal communication skills, with the ability 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, including Pandas, NumPy, and scikit-learn, or similar.
  • Experience with software development lifecycle practices, preferably Agile.
  • Good knowledge of IT systems, architectures, and terminology.
  • Strong interpersonal and leadership skills.
  • A bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or Engineering is required.
  • Five to ten years of experience in data science or machine learning, including at least three years in financial services domains and two or more years in client-facing or professional services roles.

Responsibilities

  • 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 designing client-centric solutions aligned with the company's product offering.
  • Create statements of work inputs, estimates, and technical approaches for services engagements; support pre-sales with demos, proofs of value, and solution narratives.
  • Manage the client review and sign-off process for functional documents and artefacts.
  • Take overall responsibility for documenting functional artefacts.
  • Build and evaluate models for financial services use cases such as anti-money laundering, fraud detection, alert triage, trading surveillance, credit risk, and customer intelligence.
  • Apply natural language processing and large language models, including retrieval-augmented generation, summarisation, extraction, classification, graph and network analytics, time series, anomaly detection, and ensemble methods.
  • Implement explainability, including SHAP and LIME, bias and fairness testing, performance monitoring, and model risk controls to meet regulatory and enterprise standards.
  • Deliver proofs of concept and pilots; productionise solutions with engineering using MLOps practices, including continuous integration and delivery, model registries, experiment tracking, and feature management.
  • 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 company products and client systems through APIs, microservices, and event streams, optimising for scalability, latency, and cost.
  • Implement retrieval components such as vector databases and prompt orchestration frameworks for large-language-model solutions.
  • Plan and execute user acceptance testing, training, and knowledge transfer to drive adoption and embed AI in business workflows.
  • Mentor customer and internal teams and contribute reusable assets such as templates, prompts, pipelines, and notebooks.
  • Share best practices and feedback with product and research and development teams to influence the roadmap.

Desired Qualifications

  • An understanding of compliance processes and workflows within the financial services industry.
  • Knowledge and exposure to Unix, including Solaris, AIX, Linux, and HP-UX.
  • Knowledge of financial regulatory modules, ideally including anti-money laundering, know your customer, FATCA, CRS, and related topics.
  • A master's degree or PhD.

About the Company

Sympera AI

AI-powered platform for relationship banking

Sympera AI provides an AI-powered platform for financial institutions that strengthens relationship banking. It helps banks and their relationship managers be more productive and grow client portfolios by offering financial intelligence and sales enablement tools. The platform combines market intelligence with client relationship management so bankers can uncover opportunities, monitor the health of business relationships, and choose effective strategies. This differentiates Sympera AI by offering an integrated solution that pairs data-driven insights with CRM capabilities, aimed at improving service and outcomes for clients. The company’s goal is to redefine relationship banking by using big data and AI to drive business growth and higher client satisfaction for financial providers.

Company size
11-50
Company stage
Seed
Total funding
$10M
Headquarters
New York City, New York
Founded
2024

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