Lead Machine Learning Scientist, Business Banking

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning, we would like to talk to you. Role: ALDS Mandate Skills & Competencies: Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and c

Work Experience Required: 8 - 12 Years Experience in programing (Python, R, SQL, NoSQL,Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction. Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights Drive excellent project management required to deliver complex projects, including effort/time estimation. Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders Manage the team-members, to ensure that the project plan is being adhered to over the course of the project Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates. Build a trusted advisor relationship with the IT management at clients and internal accounts leadership. Build

Banking hasn't changed much in decades. We're changing that. One product at a time. Lunar is a Nordic challenger bank building the future of financial life with AI at the core. Our engineers, designers, and product people work on problems that actually matter. Making money simpler, smarter, and more rewarding for millions of people across the Nordics. Fully licensed and founded in 2015, with offices in Copenhagen, Aarhus and Stockholm. We move fast, we build with purpose, and we're just getting started. As our new (Senior) Data Scientist you'll join our team based in Aarhus, reporting to Eugene, our Senior Engineering Manager, working to bring data and machine learning into how we prevent fraud, manage risk, and grow the business. What will you do? Design, build, and deploy machine learning and statistical models across fraud detection, transaction monitoring, loan risk assessment, customer risk scoring, and sales and lead generation Build and operate experimentation and evaluation frameworks — using tools like MLflow and Metaflow — with strong test sets and benchmarks across projects Dive into data analysis and feature engineering to keep pushing model performance further Partner closely with data engineers, analysts, and business stakeholders to define requirements and turn insight into decisions Document models, methodologies, and results clearly, and bring the latest ML and GenAI advances into how Lunar builds What are we looking for in you? Experience developing and deploying machine learning models in a production environment Proficiency in Python and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience with cloud-based ML platforms such as AWS SageMaker or Kubeflow Solid grounding in machine learning, statistical modeling, and data analysis techniques — experience in financial services or another regulated industry is a plus Strong problem-solving and communication skills, with the ability to translate technical concepts into business in

About the opportunity We are seeking an experienced Lead Technical Product Manager for our Machine Learning Platform within the Intelligent Operations Platforms segment. In this role, you will define the long term vision, platform architecture, and execution strategy for core Machine Learning infrastructure across N26. Your work will enable squads across the bank to automate risk assessments, prevent financial crime, and scale operational efficiency. Our ML Platforms team serves as the central nervous system for real-time, data-driven decisioning. We build and scale horizontal ML capabilities that allow critical functions including Financial Crime, Credit Risk, and Core Operations to execute with absolute precision at scale. As a Lead Product Manager, you will drive multi-squad strategy, transforming complex predictive models into resilient, compliant, sub-second scoring systems. In this role, you will Drive the Core ML Platform Vision: Define and execute the multi-year roadmap for the central Machine Learning platform, ensuring alignment with broader engineering architecture and executive business goals. Lead High-Volume ML Portfolios: Oversee complex predictive ML capabilities supporting high-throughput banking systems, focusing on real-time transaction monitoring, automated credit risk scoring, and operational workflow decisioning. Scale Enterprise MLOps Infrastructure: Own the platform tooling and standards across the full ML lifecycle. Drive strategic decisions around feature stores, real-time feature extraction pipelines, model registries, automated retraining triggers, and CI/CD for ML. Establish Model Evaluation and Governance: Define robust offline and online model evaluation frameworks, shadow deployment mechanics such as champion and challenger testing, and real-time monitoring for model drift, inference latency, and data quality degradation. Bridge Technical Leadership and Compliance: Partner closely with Principal Data Scientists, ML Engineers, Security

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role Payment Success helps merchants get paid and keep their cash flow reliable. We predict which payments are likely to fail, recover the money when they do, and protect merchant cash flow across our payment rails. As Engineering Manager, you will lead a cross-functional team of engineers, a designer and data scientists, building intelligent products that use machine learning and AI. You will take ownership of the payment intelligence products we have already built, and work with your team and product manager to decide what we build next. We give teams problems to solve rather than tasks to complete, so you and your team will own what gets built, how it gets built and how success is measured. You will be accountable for the quality, delivery and operation of everything the team ships, and you will look after your people through 1:1s, feedback and career development. You'll step in wherever the team needs you, and earn credibility with senior engineers and data scientists within the team and across product development. What excites you Shipping stuff: you’ll work with your tea

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role Payment Success helps merchants get paid and keep their cash flow reliable. We predict which payments are likely to fail, recover the money when they do, and protect merchant cash flow across our payment rails. As Engineering Manager, you will lead a cross-functional team of engineers, a designer and data scientists, building intelligent products that use machine learning and AI. You will take ownership of the payment intelligence products we have already built, and work with your team and product manager to decide what we build next. We give teams problems to solve rather than tasks to complete, so you and your team will own what gets built, how it gets built and how success is measured. You will be accountable for the quality, delivery and operation of everything the team ships, and you will look after your people through 1:1s, feedback and career development. You'll step in wherever the team needs you, and earn credibility with senior engineers and data scientists within the team and across product development. What excites you Shipping stuff: you’ll work with your tea