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Description:
We are looking for a seasoned Machine Learning Engineer who has real world machine learning experience. You feel equally comfortable performing data mining and machine learning tasks on your laptop as you are in large compute environments. You take pride in owning and maintaining the technical work environment. You enjoy telling the data story and are capable of communicating deep analytical insights to less experienced members of the R&D team and our customers. Lastly, you have been looking for an opportunity where you can use your passion and skills for a greater good against financial crime.
Example Responsibilities:
Collaborate with the R&D team to build a distributed cloud-based SaaS solution for Identity Document Classification and Data Extraction.
Build scalable machine learning models, algorithms, and analytics on large financial datasets (both fiat currency and cryptocurrency) to detect suspicious activity.
Maintain and improve the data pipelines which support our complex data sets.
Research new techniques, algorithms, and best practices within the industry.
Explore, evaluate, and integrate new data pipelines.
Participate in client interactions.
Skills and Experience:
Advanced degree in Statistics, Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, Operations Research, or a related field.
Proven and relevant industry experience
Business driven and result-oriented individual.
In-depth knowledge of Statistics, Probability, and Machine learning.
Supervised and unsupervised statistical techniques such as regression, clustering, dimensionality reduction.
Machine learning algorithms and concepts such as Random Forest, Boosting, SVMs, neural networks.
Experience developing computer vision based solutions.
Exposure to NLP models and techniques such as sentiment analysis, word embeddings, Latent Dirichlet Allocation (LDA) is a plus.
Fluent in Python, including data science tools such as OpenCV, TensorFlow, Pytorch, PIL, Pandas etc.
Passionate about writing reusable quality code.
Effective communication & collaboration skills.
Extra Credit:
Experience with big data technologies such as Map/Reduce, Hadoop, Hive, and Spark is a big plus.
Built backend systems using Java and Python.
Experience using cloud based solutions: AWS, GCP, Azure
Experience with ML Ops tools and practices: Docker, CI/CD etc.
Key Characteristics and Attitudes:
In a recent global survey these attributes were valued by Jumios in all locations and functions – we firmly believe in hiring for attitude as well as skill.
Friendly and supportive
Adaptable and flexible
Articulate and persuasive
High IQ and EQ
Curious and coachable
Commercially Aware
Resilient and tenacious
Big picture and the detail
