Remote Data Scientist
Remote Los Angeles Part-time Mid-level Data Science
At a glance
Mid-level Data Science role at Online River. Remote, United States · part-time.
Pay not stated Data Scientist salary
RoleData Science
SeniorityMid-level
LocationLos Angeles
WorkplaceRemote
EmploymentPart-time
PostedSep 28, 2024 · 2y ago
Role brief
remoteroles summary, based on the employer's posting.
What you'll do
- Collect and prepare datasets, checking their quality before using them for analysis
- Look for patterns in exploratory analysis, test hypotheses and build predictive machine learning models
- Make dashboards and visualizations that help communicate findings to others
- Agree on analytical goals with partner teams, share results and keep clear records of your methods
What you bring
- A bachelor's or master's degree in data science, statistics, computer science or a related field
- Practical experience analyzing data and building models, with a sound grasp of machine learning
- Programming ability in Python or R, familiarity with Pandas, NumPy or Scikit-learn, and experience using SQL and databases
Who this fits
This part-time remote role suits someone comfortable handling several projects independently. You should also be able to explain findings clearly in writing and conversation.
From the employer
We are seeking a skilled Data Scientist to join our team remotely. The ideal candidate will leverage statistical analysis, machine learning, and data visualization techniques to extract insights and inform business decisions. This role involves collaborating with cross-functional teams to define analytical requirements and deliver actionable solutions.
Data Collection & Preprocessing:
Statistical Analysis:
Model Development:
Data Visualization:
Collaboration:
Documentation:
Continuous Learning:
Data Collection & Preprocessing:
- Gather, clean, and preprocess datasets to ensure quality and integrity.
Statistical Analysis:
- Conduct exploratory data analysis to identify patterns and validate hypotheses.
Model Development:
- Develop, implement, and optimize predictive models and machine learning algorithms.
Data Visualization:
- Create visualizations and dashboards to communicate insights effectively.
Collaboration:
- Work with cross-functional teams to define project objectives and present findings.
Documentation:
- Maintain thorough documentation of analytical processes and methodologies.
Continuous Learning:
- Stay updated on data science trends and participate in professional development activities.