Profession.hu
Budapest
2M – 2.4M HUF alkalmazotti havi bruttó
Elvárások
- Java
- JVM
- Spring
- JDBC
- CD pipelines
- Machine Learning
- Machine learning
- Communication skills
- Relational database
- Angol (C2)
Előnyt jelentő készségek
- Machine Learning Model Operationalization Management
A mi követelményeink
- 6+ years of experience Java (11<) or other JVM based language, experience with Spring framework and deep understanding of JDBC and database internals
- Experience with CI/CD pipelines and Distributed and Concurrent Systems
- Experience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plus
- Fluent ENGLISH knowledge
- A strong product mindset and passion for user experience, you prioritise work with the customers in mind and make data-driven decisions to fix customer pain-points
- Experience working with relational and non-relational databases, query optimisation and designing schemas
Pozíció / projekt rövid leírása
Our TOP partner 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, our partner on a mission to make their life easier and save them money.
As part of their team, you will be helping us create an entirely new network for the world’s money. For everyone, everywhere.
Napi feladatok
- The team you will join: Servicing Machine Learning and Data Engineering
- The SMDE team at Servicing Platform is dedicated to build a platform and tooling for fincrime teams, fincrime data scientists. Our team is responsible for developing and enhancing real-time transaction monitoring systems, and data scientist focused analytical tooling.
- Software engineers, data analysts, and data scientists collaborate on a daily basis to continuously improve our systems and provide support for fincrime teams.
- Our vision is:
- Build tooling for data scientists and engineers to explore, experiment, backfill and deploy most features/data points in production.
- Provide robust offline training tools as well as datasets for model retraining.
- Strengthen the partnership between product engineering teams (KYC, Fraud prevention, AML, Screening, etc) to build a platform where teams can share data points, and reuse work
- Build tooling to aggregate data using open source frameworks like Flink and Kafka streams.
Specifikációk
- Toborzás nyelvei: magyar&angol
- Azonnali kezdés
- Határozatlan idejű szerződés
- Távmunka heti 3 nap
- Rugalmas munkaidő
Metodológia
- Munkaeszközök kiválasztásának lehetősége
Irodán belüli juttatások
- Ingyenes kávé
- Mobiltelefon
- Belső képzések
- Modern iroda
- Edzőterem
- Dog friendly office
Extrák
- Képzési költségvetés
- Magánegészségügyi ellátás
- Nemzetközi projektek
- Kis létszámú csapat
- Cafeteria
- Közlekedés térítése
- Maternity/ Paternity leave
- AYCM card
- E-car sharing service
