Data Scientist (Webinar Test 1)

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

We are looking for a skilled and innovative Data Scientist to join our analytics team. This role involves leveraging data to drive business insights, build predictive models, and support strategic decision-making. The ideal candidate is passionate about data, highly analytical, and experienced in machine learning and statistical modeling.

Key Responsibilities

• Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities, and work closely with the engineering team in the development of data products
• Execute analytical experiments to help solve problems across various domains and industries
• Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables
• Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy
• Analyze data for trends and patterns, and interpret data with clear objectives in mind
• Implement analytical models in production by collaborating with software developers and machine-learning engineers

Required Qualifications

• Education: Bachelor’s or Master’s in quantitative field such asData Science, Computer Science, Statistics, Mathematics, Engineering, or a related discipline
• Experience: 2–5 years of hands‑on experience building and deploying machine-learning solutions—especially recommender systems—in a SaaS or customer-facing environment
• Technical Proficiency: Proficient in Python (or R) and ML frameworks (scikit-learn, TensorFlow, PyTorch); expertise with data tools (SQL, Spark, Airflow) and cloud platforms (AWS, GCP, Azure)
• AI & Next-Gen Models: Demonstrated experience with embedding techniques, transformer-based models, and graph ML for large-scale recommendations

Preferred Qualifications

• Fortune 500 company
• LLM Proficiency: Hands-on experience leveraging large language models (e.g., GPT-4) for data augmentation, prompt engineering, or analytics automation