Tundra Technical Solutions is seeking an Intermediate Data Scientist to join their analytics team to analyze large datasets, extract actionable insights, and support data-driven decision-making using AWS cloud services.
Requirements
- Proficiency in Python, SQL, and data manipulation libraries (e.g., Pandas, NumPy).
- Experience with AWS services such as SageMaker, EC2, S3, Lambda, Glue, and Redshift.
- Solid understanding of machine learning algorithms and statistical modeling.
- Familiarity with version control (Git), CI/CD pipelines, and containerization (Docker).
- AWS Certified Data Analytics or Machine Learning Specialty.
- Experience with NLP, computer vision, or time-series forecasting.
- Familiarity with MLOps practices and tools.
Responsibilities
- Analyze large datasets to extract actionable insights and support data-driven decision-making.
- Design, develop, and deploy machine learning models using AWS services such as SageMaker, Lambda, Glue, and Redshift.
- Build and maintain scalable data pipelines and workflows in AWS.
- Monitor and improve model performance over time, including retraining and feature engineering.
- Create dashboards, reports, and visualizations to communicate findings to stakeholders.
- Ensure data quality, governance, and security best practices are followed.
Other
- 3–5 years of experience in data science or analytics roles.
- Strong problem-solving and communication skills.
- Experience working in Agile environments.
- Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
- Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information.
