TL;DR

Data Scientist (AI/Fintech): Activating, maintaining, and supporting clients by developing models and rules for financial risk management with an accent on data cleaning, preprocessing, feature engineering, and model tuning. Focus on fighting financial crime, protecting people, and communicating findings to stakeholders to assist in decision-making.

Location: Remote within England, United Kingdom.

Company

%hirify_global% is the world’s first RiskOps platform for financial risk management, safeguarding global commerce with an advanced cloud-based risk management platform, powered by machine learning and artificial intelligence.

What you will do

Understand, clean, and validate client data.
Preprocess data using shell scripts and programming languages like Python, Java, or Scala.
Iteratively compute features and tune parameters to improve model quality.
Communicate findings to project managers and assist in decision-making on Data Science project parts.
Collaborate with key stakeholders (data scientists, engineers, risk managers) from clients.
Work with other parts of the organization (Product, Research) to improve processes, best practices, and tooling.

Requirements

MSc or PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics or related field.
Proficient in Machine Learning (training and testing, avoiding overfit).
Knowledge of Big Data technologies such as Spark and Hadoop.
Proficiency in bash, Python, and either Java or Scala.
Knowledge of resource monitoring and runtime optimization (JVM and OS level).
English: B2 required.
Work authorization for the United Kingdom is required.

Nice to have

Knowledge of statistics or data visualization.
Knowledge of tree-based algorithms (Random Forests, XGBoost, LGBM).
Knowledge of Deep Learning algorithms.

Culture & Benefits

Collaborative team spirit spanning the globe.
Open environment encouraging new ideas and potential discovery.
Immersion into the brand with training, connections, and one-on-one time with your manager during the first 30 days.
Access to comprehensive company history, context, and team knowledge.
Equal Opportunity Employer committed to diversity.
Non-discriminatory hiring practices based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.