Remote UK Data Scientist: ML & Analytics

EasyInfoBlog.com LLC; United Kingdom; Remote; GBP 99,000 - 179,000; Full time

Benefits offered by this job

Annual $1,200 coworking stipend

Subsidized health insurance

Retirement contributions

Six months of fully paid parentalleave

Fertility assistance

Flexible vacation policy (30–40 days)

Charitable donation matching up to $10

Generous equity package

Job summary

Wave Mobile Money is seeking a Data Scientist for a remote UK-based position. You will work on credit scoring, fraud detection, and optimization projects using Python, SQL, and ML techniques.

You will collaborate with product managers and operations to translate data into actionable business insights. The role requires 5+ years in data science or analytics, fluency in English, and the ability to present findings to both technical and non-technical audiences.

Qualifications

• Bachelor's degree in a quantitative field is required.
• 5+ years experience in data science, ML, or analytics.
• Proficiency in Python, SQL, and data visualization tools.

Responsibilities

• Work on credit scoring models, fraud detection, and promotions optimization.
• Collaborate with product managers and business leaders to drive data-driven decisions.
• Partner with product and operations teams to implement insights.
• Generate insights from customer, merchant, and internal data using statistics and ML.
• Design, implement, and evaluate optimizations for operations and promotions.
• Develop data-driven heuristics and ML models to improve outcomes.
• Manage analytics projects from scoping to stakeholder communication.

Skills

Analytical thinking

Communication skills

English fluency

Education

Bachelor’s degree in quantitative field

Tools

Python

SQL

Data visualization tools

Job description

Wave Mobile Money is seeking a Data Scientist for a remote UK-based position. You will work on credit scoring, fraud detection, and optimization projects using Python, SQL, and ML techniques.

You will collaborate with product managers and operations to translate data into actionable business insights. The role requires 5+ years in data science or analytics, fluency in English, and the ability to present findings to both technical and non-technical audiences.