Summer Data Science Associate - US Based Remote

Lensa; Cincinnati (OH); Remote; USD 60,000 - 80,000; Full time

Job summary

A leading career site is seeking a Summer Data Scientist Associate to work closely with the data science team. This role involves addressing business problems through data analysis and machine learning, providing hands-on experience in data processing, statistical analysis, and model development. Candidates should be pursuing a Ph.D. or Master's in relevant fields and have some experience in Python programming.

Qualifications

• Currently pursuing a Ph.D. (1-2 years in the program) or a Master's in a related analytical discipline.
• Some experience in building end-to-end models in Python preferred.

Responsibilities

• Assist in exploring and understanding data.
• Perform ETL processes and feature engineering.
• Write Python code for visualizations and models.

Skills

Proficiency in SQL

Python programming

Statistical knowledge

Machine learning algorithms

Effective communication

Adaptability

Education

Ph.D. or Master's in Statistics, Data Science, Mathematics, Economics

Job description

Summer Data Science Associate - US Based Remote

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Job Title: Summer Data Scientist Associate

Summary of Role: As a Summer Data Scientist Associate, you will work closely with our data science team to address business problems through data analysis and machine learning. You will gain hands-on experience in collecting and processing data, performing statistical analysis, and developing machine learning models to support business decisions.

Responsibilities:

1. Assist in exploring and understanding data, taking ownership of data-related questions.
2. Perform ETL (Extract, Transform, Load) processes, aggregations, and feature engineering.
3. Write Python code to create visualizations and implement models.
4. Collaborate with other data scientists on projects, sharing knowledge and learning from the team.
5. Be open to innovative ideas and alternative problem-solving approaches.
6. Communicate and present results to non-technical stakeholders.
7. Understand IT infrastructure to ensure models can be implemented in production environments.

Experience:

1. Currently pursuing a Ph.D. (1-2 years in the program) or a Master's in Statistics, Data Science, Mathematics, Economics, or a related analytical discipline.
2. Some experience, including internships, in building end-to-end models in Python (or similar language) is preferred.

Skills:

1. Proficiency in SQL and Python programming languages (pandas, numpy, scipy, scikit-learn, etc.).
2. Basic understanding of statistical knowledge and machine learning algorithms. Exposure to deep learning is a plus.
3. Familiarity with techniques such as Linear Regression, GLM, Random Forest, GBM, XGBoost, SVM, and various segmentation methods. Knowledge of Neural Networks and proficiency in Python packages (TensorFlow, etc.) are nice to have.
4. Effective communication skills.
5. Ability to learn new skills and adapt to new challenges.