Senior Data Scientist - Portfolio Optimization & ML Systems

Jobgether; United States; Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Performance-based bonus

Attendance bonus

Private pension plan

Meal allowance

Health, dental, and life insurance

Discounts on medicines

Wellhub health partnership

Childcare subsidies

Discounts on company products

Clube Ben benefits access

Scholarship opportunities

School materials assistance

Language-learning and training access

Transportation allowance

Additional days off

Casual office environment

Job summary

Jobgether in the United States seeks an experienced data scientist to design and deploy advanced ML models for portfolio optimization, recommendations, and personalization. You will collaborate with data engineers and product teams to translate business goals into deployable solutions.

Responsibilities include building scalable data pipelines on Azure/Databricks, evaluating new methods, and mentoring junior teammates. Strong Python and Spark experience required; attractive benefits apply.

Qualifications

• Bachelor's degree in Mathematics, Statistics, Engineering, CS or related field.
• Experience applying ML in production with measurable impact.
• Strong Python for data analysis and production workflows.
• Experience with Spark/PySpark and cloud platforms (Azure/Databricks).
• Knowledge of model evaluation, validation, and experimentation frameworks.
• Experience with version control, CI/CD, automation, reproducible workflows.
• Ability to design scalable data pipelines and production ML solutions.
• Proficient use of AI coding tools responsibly and securely.
• Excellent communication and collaboration skills.
• Analytical thinking, curiosity, independence, mentoring ability.

Responsibilities

• Design, develop, and deploy ML/DL models for portfolio optimization and recommendations.
• Analyze complex datasets to identify business opportunities and insights.
• Evaluate new ML techniques to solve business challenges.
• Architect and optimize large-scale data pipelines on Azure, Databricks, Spark, PySpark.
• Build reliable pipelines with Python and PySpark, with automation.
• Ensure production-ready models balancing accuracy, stability, and scalability.
• Promote best practices for experimentation, validation, CI/CD, reproducibility.
• Collaborate with data engineers, product managers, and stakeholders.
• Mentor junior data scientists and share knowledge.

Skills

Python programming

Statistical modeling

Experimentation

Communication

Mentoring

Education

Bachelor's degree in quantitative field

Master's degree preferred

PhD advantageous

Tools

Azure

Databricks

Spark

PySpark

CI/CD

Job description

Jobgether in the United States seeks an experienced data scientist to design and deploy advanced ML models for portfolio optimization, recommendations, and personalization. You will collaborate with data engineers and product teams to translate business goals into deployable solutions.

Responsibilities include building scalable data pipelines on Azure/Databricks, evaluating new methods, and mentoring junior teammates. Strong Python and Spark experience required; attractive benefits apply.