Data Scientist

NTT DATA; Tijuana; Presencial; MXN 60,000 - 90,000; Jornada completa

Descripción de la vacante

A leading technology company in Mexico seeks a Data Scientist to analyze data and derive actionable insights. The ideal candidate will leverage advanced analytics, machine learning, and statistical methods to solve complex business problems. Required skills include proficiency in Python, R, SQL, and experience with machine learning frameworks. A Master’s or Ph.D. in a relevant field and strong communication skills are preferred. Join us to drive data-driven solutions in a collaborative environment.

Formación

• Strong knowledge of programming languages such as Python, R, and SQL.
• Proficient in statistical methods and tools for data analysis.
• Experience with machine learning frameworks and libraries such as TensorFlow, scikit‑learn, or PyTorch.
• Ability to handle large volumes of data and experience with data warehousing solutions.
• Strong understanding of business processes and translating insights into strategies.
• Excellent verbal and written communication skills.

Responsabilidades

• Design and implement statistical models and machine learning algorithms to analyze data.
• Gather data from various sources, clean and preprocess it.
• Create dashboards and visualizations to communicate findings.
• Collaborate with cross-functional teams to understand business needs.
• Stay updated with the latest industry trends in data science.

Conocimientos

Python

R

SQL

Tableau

Power BI

Statistical Analysis

Machine Learning

TensorFlow

scikit-learn

PyTorch

Educación

Master’s or Ph.D. in Data Science, Statistics, Computer Science, or a related field

Herramientas

Data warehousing solutions

Descripción del empleo

Job Summary

A Data Scientist is responsible for analyzing large sets of structured and unstructured data to derive actionable insights. This role involves using advanced analytics, machine learning, and statistical methods to solve complex business problems and support decision‑making processes.

Key Responsibilities

• Data Analysis and Modeling: Design and implement statistical models and machine learning algorithms to analyze data and predict outcomes.
• Data Collection and Processing: Gather data from various sources, clean and preprocess it for analysis.
• Visualization and Reporting: Create dashboards and visualizations to communicate findings to stakeholders and support executive decision‑making.
• Collaboration: Work closely with cross‑functional teams—including IT, marketing, and customer service—to understand business needs and deliver data‑driven solutions.
• Research and Development: Stay updated with the latest industry trends and technologies in data science and apply them to improve processes and products.

Required Skills and Qualifications

• Technical Proficiency: Strong knowledge of programming languages such as Python, R, and SQL. Experience with data visualization tools like Tableau or Power BI.
• Statistical Analysis: Proficient in statistical methods and tools for data analysis.
• Machine Learning: Experience with machine learning frameworks and libraries such as TensorFlow, scikit‑learn, or PyTorch.
• Data Management: Ability to handle large volumes of data and experience with data warehousing solutions.
• Business Insight: Strong understanding of business processes and the ability to translate data insights into actionable business strategies.
• Communication Skills: Excellent verbal and written communication skills to effectively convey complex data insights to non‑technical stakeholders.

Preferred Qualifications

• Advanced Degree: A Master’s or Ph.D. in Data Science, Statistics, Computer Science, or a related field.
• Experience: Previous experience in a similar role, preferably in the same industry.
• Certifications: Relevant certifications in data science or machine learning.

NNT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For Pay Transparency information, please refer to our policies.