ML / Data Engineer

Help us harness the power of data to drive Mamo's success 📊

Mamo is looking for a Data Engineer, who will help empower Mamo, by guiding us through the dynamic landscape of fintech with precision and insight.

You will collaborate with cross-functional teams to define, measure and comprehend key metrics, shape business strategy and product roadmap through data, produce analysis reports and models, enhance our products and services with data-driven and AI-driven approaches, and make a substantial impact on the business. 

You will work closely with the engineering team, product team and other stakeholders to determine the data collection requirements, the data schema, the data analysis, the model training and the model implementation.

Ready to shape the future with data? Dive in, and let's make waves together

👉NOTE BEFORE APPLYING

Please note that we use a tool to detect AI-generated application responses. Any applications found to contain AI-generated responses will be disqualified.

Why you’ll love working here

• Startup environment that’s big on individual responsibility and leans on process and automation.
• We’re big on culture. Work with stunning, supportive product, design and engineering teams on problems that matter.
• You will be learning and growing all of the time. From business, product, design to engineering you will be learning from a world-class team that is caring, kind, and empathetic.‍
• Mamo has the potential for a wide-reaching impact. Mamo is taking on the challenge of bringing about a new era of financial inclusion that begins close to home by providing access and experiences that make sense. That means you will never be bored.

What you will do

• Analyze large-scale structured and unstructured datasets using analytical, statistical, machine learning, or deep learning techniques to address a wide range of complex issues.
• Collaborate with stakeholders from various departments to comprehend their business requirements and obstacles, design and develop analytics solutions to achieve business goals, and facilitate decision-making.
• Partner with cross-functional teams to provide strategies based on data-driven insights across product, marketing, compliance, and other areas.
• Identify, understand, and evaluate external/internal opportunities to enhance our products and services.
• Determine and assess the success of product initiatives through goal setting, forecasting, and monitoring of key product metrics.
• Create data models, data automation systems, performance metrics, and reporting frameworks, and monitor impact over time.
• Execute Machine Learning projects from inception to completion. This encompasses understanding the business need, planning the project, collecting & exploring data, developing & validating models, and implementing ML models to generate business value.
• Present results and business impacts of insight initiatives to stakeholders within and outside of the organization.

What we’re looking for

• Adept at dissecting vague and high-level problems and coming up with solutions.
• Skilled in data extraction, analysis, and/or modeling.
• Capable of working autonomously, with minimal supervision, in a dynamic environment.
• Self-motivated, creative, team-oriented, with strong communication and presentation abilities, able to bridge business and technical audiences.
• An advocate for documentation, transparent communication, and knowledge sharing.

You have

• You have more than 5 years of professional experience with analysis tools and recommendation systems.
• Extensive experience in SQL.
• Hands-on experience with Looker Studio or similar tools.
• Solid experience in Python and data analysis libraries such as pandas, numpy, matplotlib, scikit-learn, etc …
• Experience in using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.
• Experience in developing production-grade ML systems including exploratory analysis, feature engineering, hyperparameter tuning, model training, model selection, creating data pipelines, etc.
• Knowledge of AI tools and frameworks, including off-the-shelf GenAI solution builders (e.g., OpenAI GPT Builder, Microsoft Copilot Studio), GenAI developer tools (e.g., LangChain / LangGraph, LlamaIndex), off-the-shelf ML solution builders (SageMaker, Vertex AI, ML Studio), and ML developer tools (e.g., TensorFlow, PyTorch).

Bonus if you have

• Payments, Fraud, Risk, E-Commerce or Finance background.
• Experience with Looker, BigQuery and other GCP services.