Senior Data Scientist - Fluent English

artefactlinkedin; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Remote-first Free Office arrangement.

Meal and transportation benefits (VR//

Job summary

artefactlinkedin is seeking a senior data scientist to design, build, and maintain scalable data products for analytics and decision making. You will lead end-to-end ML initiatives, mentor teammates, and contribute to an international, remote-first team operating in English.

Responsibilities include deploying models, feature engineering, data quality, and production monitoring, with collaboration across analysts, product managers, and engineers.

Qualifications

• Degree in a quantitative field such as CS, statistics, engineering, economics.
• Strong Python for data science with ML experience.
• Experience with cloud platforms and data warehouses.
• Proficient with supervised and unsupervised modeling approaches.
• Familiarity with MLOps tooling and Git-based workflows.
• Excellent communication and mentoring in an international, English-speaking team.

Responsibilities

• Design, develop, and deploy end-to-end ML models with data acquisition and feature engineering.
• Collaborate with analysts, PMs, and engineers to translate business problems.
• Engineer features from large data sets to improve accuracy and performance.
• Champion data quality and define dataset requirements for analytics.
• Monitor models for drift and performance bottlenecks; troubleshoot.
• Document methodologies and present findings to technical and non-technical audiences.
• Mentor junior data scientists and analysts through reviews and sessions.

Skills

Python

Pandas

NumPy

scikit-learn

PySpark

Cloud platform (GCP/AWS/Azure)

SQL Databases

MLOps

Databricks

Git workflows

Education

Quantitative degree

Tools

Databricks

MLflow

SageMaker

Vertex AI

GitHub

Azure DevOps

GitLab

Job description

Role overview

A senior data scientist role responsible for designing, building, and maintaining scalable data products that support analytics and decision-making across the business. The role combines hands-on machine learning engineering with technical leadership and mentoring, and is delivered through a remote-first, international team that operates in fluent English.

Responsibilities

• Design, develop, and deploy end-to-end machine learning models, covering data acquisition, feature engineering, and ongoing production monitoring.


• Collaborate with analysts, product managers, and engineers to translate business problems into data science frameworks with measurable outcomes.


• Engineer and refine complex features from large datasets to lift model accuracy and business performance.


• Champion data quality and integrity, defining dataset requirements suited for advanced analytics and modeling.


• Monitor, analyze, and troubleshoot deployed models, handling concept drift, quality degradation, and performance bottlenecks.


• Document and present methodologies, model findings, and strategic recommendations to both technical and non-technical audiences.


• Mentor junior data scientists and analysts through code reviews, design sessions, and knowledge sharing.

Requirements

• Degree in Computer Science, Statistics, Engineering, Economics, or another quantitative field.


• Strong Python skills for data science, including pandas, NumPy, scikit-learn, and PySpark.


• Hands-on experience with at least one major cloud platform such as GCP, AWS, Azure, or Databricks.


• Familiarity with data warehousing and databases such as PostgreSQL, SQL Server, BigQuery, or Snowflake.


• Practical experience with supervised models (e.g., XGBoost, logistic regression) and unsupervised approaches like clustering.


• Working knowledge of MLOps tooling such as Databricks, MLflow, SageMaker, or Vertex AI, plus Git-based workflows on GitHub, Azure DevOps, or GitLab.


• Strong communication, mentoring ability, problem-solving skills, curiosity, collaboration, and an entrepreneurial mindset, with fluent English for an international environment.

Nice to have

• Experience with a deep learning framework such as PyTorch or TensorFlow/Keras.

Benefits and work setup

• Remote-first Free Office arrangement.


• Meal and transportation benefits (VR/VT).


• Gympass, plus life, health, and dental insurance.


• Woba coworking credits usable anywhere.


• Three in-person \"Get Together\" gatherings per year with workshops, talks, training, and social time.


• Semiannual reviews offering pathways for promotion.