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Senior IT Business Analyst, Finance Platform

Bolt

As a Senior IT Business Analyst embedded in Bolt's Finance Engineering / Automations team, you will be the key link between financial stakeholders, regulatory requirements, and engineering teams. Your primary responsibility is to translate complex financial legislation, compliance obligations, and business needs into clear, structured, and traceable system requirements. You will work closely with Accounting, Tax, Controlling, Reporting, and Procurement teams, as well as engineering and product teams, ensuring that automations built at Bolt are compliant, reliable, and well-documented. Your work will directly impact Bolt's financial compliance and sustainability by helping automate critical processes and reduce significant compliance risks across global markets.

Senior II Software Engineer - Machine Learning Platform

Wise

About the company Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere. More about our mission and what we offer . The role About the role For our customers, Wise should feel as simple as sending money from A to B. Behind that simplicity is a complex engine of currencies, routes, products, and features, generating terabytes of data every day. Data Products & Insights helps Wise turn that data into products, insights, and decisions at scale. Within this area, the Machine Learning Platform (MLP) team builds and maintains the infrastructure that enables data scientists across Wise to develop, deploy, serve, and monitor machine learning models at scale. Our platform powers predictions and decisions across the business - from fraud detection to treasury management to product personalisation - directly impacting how Wise serves millions of customers worldwide. Your mission and role will be building and maintaining a cost efficient and scalable machine learning platform, that is a delight to use and that provides a good engineering and data science experience while shortening the full experimentation feedback loop - a data scientist does not just deploy models fast, but learns fast which model is better. Your input will directly affect how Wise is making decisions and predictions on billions of events. We are looking for a Senior Software Engineer to join our team in Tallinn and help us evolve from a collection of tools into a coherent, self-service platform. How we work: We are a small, collaborative team that values product thinking, shared ownership, and continuous improvement. We are in the early stages of introducing structured agile practices and treat every process change as an experiment. The MLP team is part of the Data Products & Insights Squad. We own the infrastructure layer that sits between data scientists and production: model serving, training pipelines, model registry and experiment tracking, feature management, and model monitoring on the line. Our customers are internal - Data Scientists and ML engineers across Wise - and our success is measured by how effectively they can build, deploy, and iterate on models without friction. What will you be working on? Building and maintaining core ML platform services including model serving infrastructure, training pipelines, and experiment tracking Contributing to the evolution of our platform from individual service offerings towards a coherent, user-driven product Improving platform scalability, reliability, and operability, ensuring our infrastructure can support hundreds of models in production while making pragmatic trade-offs around cost, complexity, and user needs. Improving observability and monitoring across the model lifecycle, helping data scientists understand model health and performance Collaborating with data scientists to understand their workflows, pain points, and needs - treating them as your customers Participating in on-call/support rotation, contributing to platform stability and identifying opportunities to reduce operational toil Helping shape the technical and product roadmap by contributing to discovery, spikes (exploratory/investigative work), and architectural decisions Sharing knowledge across the team, reduce silos, mentor others, and help raise engineering standards through design reviews, code reviews, documentation, and continuous improvement. What does it take? You care about bringing value and satisfaction to your customers - the developer/user experience of the people who use your platform matters as much as the technical elegance of the solution You think in systems, not just features - you consider how components interact, where complexity lives, and how to reduce it You are comfortable working across the stack - from infrastructure and orchestration to APIs and developer tooling You take ownership of problems end-to-end, from understanding the need through to production and beyond You communicate clearly, build consensus, and enjoy collaborating with people from different disciplines - data scientists, product managers, and fellow engineers You have a growth mindset - curious, experimental, and open to giving and receiving regular feedback You share your ideas, continuously improve yourself and the team around you, and are comfortable working collaboratively in a hybrid environment What do you need? We are fully aware that it is uncommon for a candidate to have all skills required and we fully support everyone in learning new skills with us. We value potential and enthusiasm as much as existing expertise. So if you have some of those listed below and are eager to learn more we do want to hear from you! Strong engineering background in Python with experience building and maintaining production systems Experience with Kubernetes - deploying, managing, and troubleshooting containerised workloads Familiarity with ML platform tooling such as MLflow, Airflow, or similar orchestration and experiment tracking frameworks Experience with cloud infrastructure (AWS or GCP) including compute, storage, and networking Understanding of distributed systems principles - you know the trade-offs between different architectures and can make pragmatic decisions Experience with observability and monitoring - building dashboards, alerts, and tooling that helps teams understand system health Solid understanding of software engineering best practices - testing, code review, CI/CD, and clean, maintainable code Ability to use AI-assisted development tools responsibly, while validating outputs and retaining ownership of code quality. Nice to haves Experience building or contributing to internal developer platforms or self-service tooling Familiarity with ML workflows - training, serving, feature engineering, model monitoring (you don't need to be a data scientist, but understanding the domain helps) Experience with Infrastructure as Code (Terraform, CDK, or similar) Exposure to streaming or batch data processing frameworks (Spark, Flink, Kafka) Interest in platform-as-product thinking - treating adoption, user experience, and feedback loops as first-class concerns What you get back The opportunity to shape a platform that directly enables ML-driven decisions across a global financial product serving millions of customers A team that values autonomy, experimentation, and continuous improvement - where your ideas about how we work matter as much as what we build Real ownership of the systems you work on - from architecture decisions to production operations Exposure to complex, real-world ML infrastructure challenges at scale A collaborative environment where people are grounded, driven, and genuinely enjoy working with others Interested? Find out more: How we work – a practical guide DEI @ Wise Wise Tech Stack (2025 update) What do we offer: Starting salary: gr. 85,000 - 108,000 EUR + RSUs Wise Benefits #LI-AB3 #LI-Hybrid Our Engineering career map Wise Engineering – https://medium.com/wise-engineeri Additional information For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive. We're proud to have a truly international team, and we celebrate our differences. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers. If you want to find out more about what it's like to work at Wise visit Wise.Jobs . Keep up to date with life at Wise by following us on LinkedIn and Instagram .

Finance Data Analyst

Bolt

As a Finance Data Analyst, you’ll transform financial data into insights that power smarter decisions and real-world impact. This role is all about turning numbers into action - automating data flows, uncovering trends, and helping our teams make data-driven decisions faster and better. You’ll collaborate across departments to refine and improve financial processes, build insightful dashboards, and ensure everything runs seamlessly behind the scenes. In this fast-paced environment, you’ll be the go-to expert for clean, accurate data and clear, actionable insights -driving change and making a difference.

WFM Operations Partner Lead

Wise

About the company Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere. More about our mission and what we offer . The role We’re looking for a Workforce Management Operations Partner Lead to join our Operational team in our Tallinn, Estonia office! The WFM Operations Partner Lead is the primary interface between Workforce Management and Operations , responsible for ensuring that WFM disciplines are consistently understood, adopted, and applied in operational decision-making. This role does not execute tactical WFM activities such as intraday moves, schedule creation, or capacity modelling. Instead, it acts as a business partner and discipline guardian, translating WFM insights into clear operational trade-offs and constructively challenging decisions that undermine workforce plans. The Network: This is an individual contributor (IC) role with a "capability multiplier" mandate. While they do not have direct reports, they provide dotted-line mentorship and coaching to Intraday and Scheduling Specialists to improve their decision-quality. Team Goal: To protect the scalability of Wise. The team’s mission is to ensure that WFM insights are actually adopted and applied, ensuring we hit our SLAs efficiently as the company grows. Your Mission Your mission is to shift Operations from reactive, short-term workforce decisions toward planned, data-driven execution, ensuring intraday, scheduling, and capacity principles are applied consistently to protect service, cost, and scalability outcomes. This role is not accountable for forecast accuracy, schedule creation, or intraday execution, which remain the responsibility of WFM execution teams. In addition, the WFM Operations Partner serves as a mentor and capability multiplier for Intraday and Scheduling Specialists, supporting their professional development and decision quality through guidance, coaching, and feedback, while maintaining a dotted-line connection rather than direct people management accountability. The candidate will focus on these high-priority initiatives immediately upon joining: Stakeholder Transition: Moving Operations leaders away from "gut-feel" staffing decisions toward the Service Scale operating principles and WFM playbooks. Governance Framework: Auditing and surfacing recurring "exceptions" or manual overrides in scheduling to identify where WFM discipline is breaking down. Decision-Quality Coaching: Running "mentor clinics" for Intraday and Scheduling Specialists to help them think about long-term trade-offs rather than just short-term fixes. Scenario Steering: Facilitating structured "What-If" conversations with Ops leads regarding upcoming demand spikes or staffing constraints, ensuring they understand confidence ranges rather than just "point estimates." Qualifications 2–4 Years WFM/Ops Experience: Proven track record in high-volume, scaled environments (Contact Centers or Shared Services). Financial Services Knowledge: Specific understanding of KYC, FinCrime, or regulated operational environments. The "Translator" Ability: Capable of turning complex WFM jargon (Erlang, Shrinkage, Occupancy) into clear, actionable business advice. Strategic Assertiveness : The backbone to constructively challenge senior leaders and say "no" when decisions undermine WFM plans Analytical Reasoning: Ability to interpret data trends and identify leading vs. lagging indicators rather than just reading metrics. Stakeholder Management: Experience acting as a partner rather than just a reporting function; comfortable operating with Heads of Departments. Forward-Looking Mindset: A bias toward proactive risk identification and prevention rather than reactive firefighting. Change Management: Experience driving the adoption of new playbooks or frameworks across different operational units. Prior WFM experience Schedule optimization experience / knowledge on how is it done Soft skills required: Strong stakeholder management. Welcome challenges with a positive attitude. Easily adapt to changes. Extremely guided towards teamwork/collaboration. Flexible to work weekends/Public Holidays Nice to have: Tool Proficiency: Functional familiarity with WFM software (e.g., Calabrio, NICE, Verint) to understand outputs and constraints. Coaching & Mentorship: Experience in a lead or mentor capacity, specifically helping others improve their decision-making quality. SQL or Data Viz Skills: Ability to self-serve data using tools like Looker to verify trends before stakeholder meetings. Additional information Compensation: 3 450 - 4 500 EUR gross monthly + RSU (Restricted Stock Units) For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive. We're proud to have a truly international team, and we celebrate our differences. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers. If you want to find out more about what it's like to work at Wise visit Wise.Jobs . Keep up to date with life at Wise by following us on LinkedIn and Instagram .

Senior Product Designer, Incentives, Merchants Ads

Bolt

We’re looking for a skilled Senior Product Designer to take full ownership of the incentives experience across the Merchants domain. Your main objective will be to help evolve and optimise the flows and merchants-facing mechanics for ads and campaigns management. This is a hands-on individual contributor role with strong cross-functional collaboration.

Product Manager, Micromobility Growth and Pricing

Bolt

$212

Senior Product Manager, Micromobility Compliance and Expansion

Bolt

$221

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