Data Scientist (Remote - Mexico Only)

Scalepex is a dynamic services firm specializing in providing nearshore solutions for premium brands like Nike, Pepsi, Toyota, Virgin, and Walgreens. Our mission is to connect prominent market leaders with top-tier professionals from around the world, fostering collaboration, efficiency, and growth.

As a Data Scientist at Scalepex, you will play a pivotal role in analyzing complex datasets to derive actionable insights that drive business decisions. You will collaborate with cross-functional teams to develop and deploy machine learning models, ensuring data-driven strategies align with client objectives in a fully remote environment.

• → Data Analysis & Modeling: Apply advanced statistical analysis and machine learning techniques to extract insights from large, complex datasets.
• → Model Development: Design, develop, and deploy predictive models, optimization systems, and other machine learning products.
• → Data Visualization: Create compelling visualizations to communicate findings to both technical and non-technical stakeholders.
• → Collaboration: Work closely with data engineers and data architects to integrate models into production systems.
• → Project Leadership: Lead end-to-end data science projects, ensuring alignment with business objectives and stakeholder requirements.

• Experience: Minimum of 3 years of hands-on experience as a Data Scientist or Data Analyst.
• Technical Skills:
• Proficient in programming languages such as Python and/or R.
• Experience with SQL and relational databases.
• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with data visualization tools like Power BI or Tableau.
• Education: Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field. A Master's degree or advanced certification is preferred.
• Soft Skills:
• Strong problem-solving and analytical skills.
• Excellent communication skills in English.
• Ability to work independently in a remote setting.

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with big data processing tools like Spark or Hadoop.
• Knowledge of Natural Language Processing (NLP) techniques.
• Experience in deploying machine learning models using platforms like Databricks or MLflow.