Senior AI Data Scientist: Predictive Modeling Leader

Placements24; Willows (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Placements24 is seeking a Senior AI Data Scientist to lead predictive modeling and advanced analytics initiatives. You will develop, train, and deploy sophisticated machine learning models using large datasets to drive strategic decisions.

The role requires expertise in statistical modeling, ML algorithms, and data manipulation, with responsibilities spanning the full data science lifecycle from data acquisition to model deployment and monitoring.

Qualifications

• Master's or PhD in a quantitative field.
• 5+ years of experience building and deploying predictive models.
• Proficiency in Python or R and common data science libraries.
• Strong knowledge of ML algorithms and time series analysis.
• Experience with SQL and big data technologies is a plus.
• Excellent communication and problem-solving skills.

Responsibilities

• Develop, train, and deploy ML models for predictive tasks.
• Perform exploratory data analysis to identify trends and anomalies.
• Clean, preprocess, and transform large, complex datasets from various sources.
• Engineer features to improve model performance.
• Collaborate with stakeholders to translate business needs into data science problems.
• Communicate insights via visualizations and reports.
• Mentor junior data scientists and stay updated with advancements.
• Stay current with latest data science techniques.

Skills

Python

R

Machine learning

Statistical modeling

Data visualization

SQL

Big data (Spark/Hadoop)

Team leadership

Education

Master's or Ph.D. in a quantitative field

Tools

pandas

NumPy

scikit-learn

TensorFlow

PyTorch

Job description

Placements24 is seeking a Senior AI Data Scientist to lead predictive modeling and advanced analytics initiatives. You will develop, train, and deploy sophisticated machine learning models using large datasets to drive strategic decisions.

The role requires expertise in statistical modeling, ML algorithms, and data manipulation, with responsibilities spanning the full data science lifecycle from data acquisition to model deployment and monitoring.