Associate Data Scientist (bi-lingual, onsite, Mexico City Office)

Overview:

We are seeking a highly motivated and detail-oriented Associate Data Scientist to join our innovative team. This entry-level role is ideal for recent graduates or individuals with limited experience in data science but with a strong passion for data and a keen interest in the healthcare industry. The Associate Data Scientist will work under the guidance of senior team members to support the development and deployment of data-driven solutions. If you are passionate about data and eager to solve complex problems, we encourage you to apply.

Data Collection and Cleaning:

• Assist in collecting data from various sources, including databases, web scraping, and public datasets.
• Clean and preprocess data to ensure quality and usability for analysis.

Data Analysis:

• Perform exploratory data analysis (EDA) to identify patterns, trends, and insights.
• Apply basic statistical methods to analyze data and generate preliminary reports.

Model Building:

• Support the development of machine learning models to solve business problems.
• Assist in evaluating model performance and making improvements.

Feature Engineering and Deployment:

• Contribute to feature identification and testing, implementing feedback loops to refine models.
• Assist in preparing models for deployment, working closely with production operations to monitor performance.

Data Visualization:

• Create visualizations and reports to effectively communicate data insights to stakeholders using tools like Matplotlib, Seaborn, Tableau, etc.

Collaboration:

• Work closely with cross-functional teams, including data engineers, business analysts, and other stakeholders.
• Participate in team meetings and contribute to data-driven solutions.

Documentation:

• Document data processes, models, and analyses, ensuring reproducibility and knowledge sharing.

Customer Engagement:

• Assist in engaging with customers to identify opportunities for integrating data insights into their decision-making processes.

Best Practices:

• Learn and share best practices in structured problem-solving and data analysis.
• Complete all responsibilities as outlined in the annual performance review and/or goal setting. Required
• Complete all special projects and other duties as assigned.  Required

It is expressly understood that the aforementioned obligations and responsibilities are not exhaustively stated, so that the Employee must comply with all other functions, obligations and responsibilities, limitations or instructions of the Company that derive from everything related to his main activities and without additional compensation since the Employee's salary already includes any compensation required. This job description is intended to describe the general nature and level of work being performed and is not to be construed as an exhaustive list of responsibilities, duties and skills required.

Education:

• Bachelor’s degree in a relevant field (e.g., Data Science, Computer Science, Statistics, Mathematics, Engineering).

Technical Skills:

• Proficient in programming languages such as Python.
• Experience with SQL for database querying.
• Experience with machine learning libraries (e.g., Scikit-Learn, TensorFlow, PyTorch) and data visualization tools and libraries (e.g., Matplotlib, Seaborn, Tableau, etc.).

Analytical Skills:

• Strong problem-solving skills and the ability to think analytically.
• Understanding of statistical methods and their applications.

Communication Skills:

• Ability to communicate complex data findings in a clear and concise manner.
• Good written and verbal communication skills.
• Fully bilingual in English and Spanish (written and verbal).

Soft Skills:

• Attention to detail and a commitment to accuracy.
• Ability to work both independently and as part of a team.
• Curiosity and a willingness to learn and adapt to new technologies and methods.

Minimum Experience:

• 1-2 years of experience in data science or related fields, with internships or academic projects considered.

Preferred Qualifications:

• Internship or project experience in data science or related fields.
• Familiarity with big data technologies like Hadoop or Spark is a plus.
• Familiarity with version control systems like Git.
• Familiarity with JIRA or other product management tools is a plus.
• Proficient in Microsoft Office (PowerPoint, Excel, Word).