Senior Data Scientist - Real-Time ML (Remote)

Jobgether SRL; Italia; Remote; EUR 136,000 - 183,000; Full time

Benefits offered by this job

Competitive compensation (US range)

Fully remote working environment

Front-row ML problems

Globally distributed team

Data-driven culture

Job summary

Jobgether SRL currently seeks a Senior Data Scientist to join a remote, Italy-based team developing high-volume, real-time browser and device identification systems. You will lead end-to-end data science initiatives, from research to production deployment, tackling noisy unlabeled data and complex ML challenges in a highly technical environment.

The role emphasizes collaboration across data science, engineering, and backend development, with on-call rotation and strong emphasis on Go, SQL, and

Qualifications

• 5+ years of professional experience spanning machine learning, data science, and backend development or closely related engineering disciplines.
• Advanced knowledge of machine learning fundamentals and statistical methodologies.
• Strong practical experience with supervised learning, including gradient boosting and approaches for high-cardinality categorical data.
• Hands-on experience with semi-supervised and unsupervised learning techniques.
• Strong exploratory data analysis and creative problem-solving skills, particularly with incomplete, noisy, or unlabeled datasets.
• Proven experience developing real-time machine learning services, including model inference and integration between models and production applications.
• Ability to transform machine learning models into minimum viable real-time web services and production-ready solutions.
• Excellent coding and software engineering skills, including strong SQL capabilities and familiarity with Git, CI/CD pipelines, IDEs, and shell scripting.
• Strong communication skills and fluent English, with the ability to collaborate effectively in a distributed international environment.
• Experience with data platforms and tools referenced in the benefits section is advantageous.

Responsibilities

• Develop data-driven algorithms using raw, noisy, and unlabeled data to improve browser and device identification capabilities.
• Design and implement supervised, semi-supervised, and unsupervised machine learning approaches, including methods for high-cardinality categorical data.
• Own data science initiatives end to end, from problem definition and experimentation through production deployment and integration with real-time services.
• Design experiments and technical solutions for real-time inference, model-to-service integration, training automation, and other machine learning engineering challenges.
• Conduct exploratory data analysis to investigate business and technical questions, identify anomalies, and evaluate model and dataset performance.
• Develop practical approaches for collecting and evaluating data when labeled datasets are limited or unavailable.
• Contribute to an engineering-focused, data-driven culture by sharing tools, methodologies, and effective data science practices with colleagues.
• Collaborate across data science and engineering functions to turn machine learning concepts into reliable, production-ready services.
• Participate in a shared on‑call rotation, with schedules communicated in advance and coverage designed to minimize disruption outside normal working hours.

Skills

Machine learning

Data science

Backend development

SQL

Go

Distributed systems

Tools

Go

ClickHouse

Snowflake

BigQuery

dbt

Superset

Tableau

Looker

Pinecone

FAISS

Qdrant

AWS

Job description

Jobgether SRL currently seeks a Senior Data Scientist to join a remote, Italy-based team developing high-volume, real-time browser and device identification systems. You will lead end-to-end data science initiatives, from research to production deployment, tackling noisy unlabeled data and complex ML challenges in a highly technical environment.

The role emphasizes collaboration across data science, engineering, and backend development, with on-call rotation and strong emphasis on Go, SQL, and