Engineering Manager - Risk

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Do you ever get frustrated about how much fraud there is online and how little banks seem to be able to do to stop it? This is your chance to make a difference and level the playing field!

We are looking for an Engineering Manager to join our team in Poland!

Antifraud and Risk Management is heavily invested as one of the strategic growth areas for GeoComply in the next 3 years. The engineering team is currently in a hypergrowth state, starting with 1 team in Q4 2021 and expanding to 4 teams by Q2 2022. We are building a new generation of Anti-fraud product suite that helps different businesses detect, prevent, and eliminate fraud in the end-to-end user journey, including sign-up, authentication, financial funding, and order. The product uses advanced machine learning techniques in combination with strong data fusion from geolocation, device, network, and user behaviour data to achieve a highly accurate fraud detection rate. We are looking for Engineering Leaders with a proven track record of building and scaling engineering teams to drive product evolution and capitalize on future growth opportunities.

As an Engineering Manager, you will lead a full-stack software engineering team, including Web and Backend engineers. Together with a Product Manager, you will shape, drive, and execute the roadmap of your product. You will partner with many teams, including Data Science, Account Management, QA, UI/UX, Customer Support to align your team’s goals with cross-team's support and to work toward a bigger goal of bringing value to GeoComply’s customers. You are responsible for hiring and developing career paths for your team members - it will be critical to foster a positive cross-team culture that collaborates across remote offices (Asia, North America, and Europe). 

What You Will Be Doing

• Collaborate with product manager & cross-functional team to determine the product roadmap that aligns with the broader company vision;
• Be responsible for the technical architecture and execution/delivery of projects that meet the business objectives;
• Define and continuously optimize your team’s working model (sprint/agile processes) for efficiency & quality;
• Manage & lead the team through critical projects;
• Provide sound judgement on hard tradeoffs between scopes, engineering capacity, and time constraints; 
• Set a high bar for engineering talent recruitment;
• Coach, develop, and grow your engineering team to make bigger impacts and job satisfaction;
• Build a strong culture of teamwork, guide team members to resolve conflicts and help build a cohesive relationship.

About You

• 5+ years of professional software development experience;
• 2+ years of management experience leading software engineers;
• Strong communication, leadership, and problem-solving skills;
• Track record of managing, recruiting, and retaining strong engineering talent and growing effective teams;
• Experience working with multi-functional, globally distributed teams to coordinate work and deliver solutions that span multiple teams;
• Experience working with PMs, designers, data scientists, and infrastructure teams to identify opportunities, prioritize roadmaps, and solve problems;
• Strong technical skills with experience in large-scale, distributed systems, including SQL/NoSQL storage, transactional updates, asynchronous processing with message queues like Kafka, logging, system monitoring, and performance tuning;
• Desire knowledge of microservices, distributed systems.

Bonus Points if You

• Experience with distributed systems, microservices implementation, such as Golang, Scala;
• Experience or having domain knowledge in online payment, eCommerce, credit card processing, risk management, or fraud detection (big plus);
• Experience with Data Analysis and Data Processing using big data technologies: ELK stack (Elasticsearch, Kibana), DataLake, Spark, Hadoop;
• Skilled in Data Science or Machine Learning.