[Work From Home] Data Scientist | Fully Remote US
remote zest jobsRemoteFull Time1w ago
PythonGoRMachine LearningNLPAIData ScienceTalentSolutionsCommunityEngineeringPlatform
Job description
Data Scientist | Fully Remote US
About the role
This position will involve developing advanced algorithms and models to enhance hiring products. You will analyze complex datasets to uncover actionable insights and contribute to the creation of new data-driven features. The role requires translating business needs into analytical projects and communicating findings effectively.
Key facts
What you'll do
- Construct and refine machine learning models and algorithms to improve product functionality.
- Examine user interaction data and decision-making patterns to identify key trends.
- Define new performance indicators and design algorithms for innovative product offerings.
- Plan and conduct experiments to validate new product concepts.
Requirements
- A minimum of 2 years of professional experience in data science.
- A degree in a quantitative field such as Statistics, Mathematics, Computer Science, Physics, or Engineering; a Master's or PhD is preferred.
- Demonstrated experience with machine learning algorithms, including model assessment and tuning.
- Proficiency in Python, including libraries like numpy, scikit-learn, and pandas.
- Ability to transform business goals into concrete analytical tasks.
- Capacity to clearly present findings to diverse audiences.
Nice to have
- Experience with algorithmic fairness principles.
- Familiarity with recommender systems.
- Knowledge of modern Natural Language Processing techniques, such as embedding models.
- Experience collaborating with Industrial-Organizational Psychology professionals.
Skills & tools
- Python
- numpy
- scikit-learn
- pandas
- Machine Learning algorithms
- NLP techniques
Practical notes
- This is a fully remote position.
- The company offers flexible working hours.
- A Bring Your Own Device (BYOD) policy is in place, utilizing User Enrollment to separate work and personal data.