Overview
Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)
50% Travel
Skills
python
data science
data analytics
statistical analysis
machine learning
data visualization
data quality
data integrity
data pipelines
Job Details
Role: Python Data Scientist
Location: Woodland, CA (Onsite Hybrid 2 days)
Only locals required
Experience: 10+ years
Candidate must show the DL copy on video at the time of submission
About Role:
- Seeking a Senior Specialist with 7 to 11 years of experience in Python for Data Science to drive data driven insights and advanced analytics solutions.
Job Description
- Utilize advanced Python programming skills to analyze complex datasets and develop predictive models Apply data science techniques including statistical analysis machine learning and data visualization to extract meaningful insights Collaborate with crossfunctional teams to understand business requirements and translate them into technical solutions using Python Ensure data quality and integrity by implementing robust data preprocessing and cleaning methodologies Stay updated with the latest trends and advancements in Python based data science tools and frameworks Develop scalable and efficient data pipelines to support analytics and reporting needs Mentor junior data scientists and provide technical guidance within the PythonData Science domain
Roles and Responsibilities
- Design develop and deploy machine learning models and algorithms using Python Lead data science projects from concept to implementation ensuring timely delivery and quality outcomes Perform exploratory data analysis to identify patterns trends and opportunities for business improvement Collaborate with stakeholders to define key performance indicators and success metrics Optimize existing data science workflows and models for better performance and accuracy Document methodologies code and findings to ensure reproducibility and knowledge sharing Support the integration of data science solutions into production environments Drive continuous improvement initiatives by evaluating new tools and technologies relevant to Python and data science
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