Data Scientist: ML & Big-Data for Product Insights

GSOBA; Los Angeles (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

GSOBA is seeking a skilled Data Scientist to join our analytics team in Los Angeles. You will drive business insights by building predictive models, evaluating experiments, and collaborating with engineers to deploy data products.

You should have 2–5 years in ML, strong Python/R skills, and experience with SQL, Spark, Airflow, and cloud platforms. Passion for data and scalable solutions is essential.

Qualifications

• Degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, or Engineering.
• 2–5 years hands-on experience building and deploying machine-learning solutions, especially recommender systems, in SaaS or customer-facing environments.
• Proficient in Python (or R) and ML frameworks (scikit-learn, TensorFlow, PyTorch); skilled with data tools (SQL, Spark, Airflow) and cloud platforms (AWS, GCP, Azure).
• Experience with embedding techniques, transformer-based models, and graph ML for large-scale recommendations.

Responsibilities

• Lead data strategy to identify and integrate new datasets for product capabilities.
• Execute analytical experiments to solve problems across domains.
• Identify data sources and collect large structured/unstructured datasets.
• Devise and utilize algorithms and models to mine big-data stores; clean data for accuracy.
• Analyze data for trends and interpret with clear objectives.
• Collaborate with developers to implement analytical models in production.

Skills

Python

R

ML frameworks

Experimentation

Data modelling

Big data analytics

Education

Bachelor's or Master's in quantitative field

Tools

SQL

Spark

Airflow

AWS

GCP

Azure

Job description

GSOBA is seeking a skilled Data Scientist to join our analytics team in Los Angeles. You will drive business insights by building predictive models, evaluating experiments, and collaborating with engineers to deploy data products.

You should have 2–5 years in ML, strong Python/R skills, and experience with SQL, Spark, Airflow, and cloud platforms. Passion for data and scalable solutions is essential.