Data Scientist

ADI Global Distribution; Santiago de Querétaro; Híbrido; MXN 600.000 - 900.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Benefits beyond local labor law

Collaborative environment

Growth and training opportunities

Descripción de la vacante

ADI Global Distribution seeks a Data Scientist to design, build, and operationalize advanced data science and ML solutions across customer experience, demand forecasting, and operations. You will translate complex data into actionable insights and move models from experimentation to production with robust MLOps practices.

The role emphasizes collaboration with engineering, analytics, and business teams, applying DL/transformer models, and delivering measurable business impact in a global, hybrid

Formación

• 3+ years of hands‑on experience in applied data science and machine learning, ideally within B2B, Retail, or Digital Commerce environments.
• Strong proficiency in Python, including experience with data science and ML libraries such as Pandas, NumPy, Scikit‑learn, and visualization tools.
• Advanced SQL skills, including the ability to write complex queries, procedures, and analytical transformations.
• Solid understanding of classical machine learning algorithms and their real-world business applications.
• Strong analytical, critical-thinking, and problem-solving abilities with a consistent focus on business impact.
• Professional working proficiency in English for global collaboration and technical communication.

Responsabilidades

• Design, develop, and deploy predictive and prescriptive models to support customer experience optimization, demand forecasting, operations efficiency, and customer behavior analysis.
• Apply a range of machine learning and AI techniques, including classical algorithms, deep learning architectures, and emerging AI approaches to solve complex business problems.
• Build, maintain, and optimize customer-facing and internal analytical models, such as recommendation systems, churn prediction, propensity modeling, customer segmentation, demand forecasting, matching, and assortment optimization.
• Perform feature engineering, clustering, statistical modeling, and time-series analysis using structured and unstructured data sources.
• Transition models from exploratory research environments into production-ready artifacts, including APIs, serialized models, and containerized solutions.
• Collaborate closely with engineering teams to ensure end-to-end MLOps integration, including CI/CD pipelines, model versioning, automated deployment, monitoring, and retraining strategies.
• Conduct advanced statistical analysis to identify trends, anomalies, and opportunities, delivering actionable insights through reports and analytical outputs.
• Support experimentation initiatives through A/B testing, KPI definition, causal inference, and measurement of business impact.
• Partner with product, engineering, analytics, and business stakeholders to identify and prioritize data science opportunities aligned with organizational goals.
• Communicate findings clearly, including assumptions, limitations, trade-offs, and recommendations, to both technical and non-technical audiences.
• Contribute to a strong data-driven culture by sharing knowledge, promoting best practices, mentoring peers, and advocating for responsible and ethical use of AI.

Conocimientos

Python

SQL

English proficiency

Analytical thinking

Herramientas

Pandas

NumPy

Scikit-learn

Descripción del empleo

Job Description

As a Data Scientist, you will collaborate with a global, high‑performing team to design, build, and operationalize advanced data science and machine learning solutions. Your work will support customer experience, demand generation/forecasting, operations optimization, and revenue growth initiatives across B2B, and Digital Commerce environments.

Job Description

As a Data Scientist, you will collaborate with a global, high‑performing team to design, build, and operationalize advanced data science and machine learning solutions. Your work will support customer experience, demand generation/forecasting, operations optimization, and revenue growth initiatives across B2B, and Digital Commerce environments.

This role sits at the intersection of advanced analytics, applied machine learning, and business strategy. You will translate complex data and modeling outcomes into actionable insights while ensuring that models move efficiently from experimentation into scalable, production‑ready solutions.

JOB DUTIES:

• Design, develop, and deploy predictive and prescriptive models to support customer experience optimization, demand forecasting, operations efficiency, and customer behavior analysis.
• Apply a range of machine learning and AI techniques, including classical algorithms (e.g., Gradient Boosting, Random Forests, SVMs), deep learning architectures (e.g., LSTM, Transformers), and emerging AI approaches to solve complex business problems.
• Build, maintain, and optimize customer-facing and internal analytical models, such as recommendation systems, churn prediction, propensity modeling, customer segmentation, demand forecasting, matching, and assortment optimization.
• Perform feature engineering, clustering, statistical modeling, and time-series analysis using structured and unstructured data sources.
• Transition models from exploratory research environments (e.g., notebooks) into production-ready artifacts, including APIs, serialized models, and containerized solutions.
• Collaborate closely with engineering teams to ensure end-to-end MLOps integration, including CI/CD pipelines, model versioning, automated deployment, monitoring, and retraining strategies.
• Conduct advanced statistical analysis to identify trends, anomalies, and opportunities, delivering actionable insights through reports and analytical outputs.
• Support experimentation initiatives through A/B testing, KPI definition, causal inference, and measurement of business impact.
• Partner with product, engineering, analytics, and business stakeholders to identify and prioritize data science opportunities aligned with organizational goals.
• Communicate findings clearly, including assumptions, limitations, trade-offs, and recommendations, to both technical and non-technical audiences.
• Contribute to a strong data-driven culture by sharing knowledge, promoting best practices, mentoring peers, and advocating for responsible and ethical use of AI.

YOU MUST HAVE:

• 3+ years of hands‑on experience in applied data science and machine learning, ideally within B2B, Retail, or Digital Commerce environments.
• Strong proficiency in Python, including experience with data science and ML libraries such as Pandas, NumPy, Scikit‑learn, and visualization tools.
• Advanced SQL skills, including the ability to write complex queries, procedures, and analytical transformations.
• Solid understanding of classical machine learning algorithms and their real-world business applications.
• Strong analytical, critical-thinking, and problem-solving abilities with a consistent focus on business impact.
• Professional working proficiency in English for global collaboration and technical communication.

WE VALUE:

• Experience applying deep learning techniques, including sequence models (LSTM) and Transformer-based architectures.
• Hands‑on experience leveraging Large Language Models (LLMs) for use cases such as text classification, search, summarization, enrichment, or automation.
• Practical experience designing or improving recommendation systems and personalization models.
• Familiarity with MLOps best practices, including CI/CD pipelines, automated testing, deployment, monitoring, and retraining.
• Experience with Snowflake or similar cloud-based data warehouse platforms.
• Exposure to data engineering concepts, such as data pipelines, dbt, workflow orchestration, or streaming architectures.
• Experience working with Azure cloud services and ML/AI platforms.
• Proficiency with GitHub for version control and collaborative development workflows.
• Experience working in Agile/Scrum environments.
• Strong collaboration skills, intellectual curiosity, adaptability, and a commitment to continuous learning.

WHAT'S IN FOR YOU:

• Benefits that go beyond Mexican labor law, ensuring your well-being and peace of mind.
• A collaborative and inclusive work environment where your contributions are valued.
• Opportunities for continuous professional growth and skill development through training, mentoring, and challenging projects.
• Access to cutting‑edge tools, resources, and a supportive team to help you excel.
• The chance to work with a global, innovative company shaping the future in its industry.

About Us

ADI is a leading global distributor and solutions provider of security, AV, and smart living technologies, helping professionals deliver smarter, safer, and more connected experiences for homes and businesses around the world. Through trusted brands, exclusive solutions, and strong industry partnerships, ADI supports more than 110,000 customers across residential and commercial markets globally. From security and video surveillance to networking, audio, automation, fire, and connected technologies, ADI offers a broad portfolio of products, services, and software designed to support the evolving needs of integrators, installers, and technology professionals. With a global team spanning operations, sales, supply chain, digital, customer experience, engineering, and more, ADI combines deep industry expertise with innovation and service to help customers grow and succeed in an evolving industry. At ADI, our teams help create the technologies, partnerships, and experiences that keep people connected, protected, and supported every day. Learn more at www.adiglobal.com .

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JOB INFO

Job Identification : 19067

Job Category : Data Management

Posting Date : 2026-08-05T18:04:16+00:00

Job Schedule : Full time

Locations : Avenida Palmira No 351. 5to Piso, San Luis Potosi, 78295, MX

(Hybrid)

Incentive Eligible : N/A

Business : ADI Global Distribution

Hiring Salary Range : We are committed to inclusive and equitable compensation. Salaries are determined by factors like role responsibilities, candidate qualifications, and geographic location. We also provide additional benefits tailored to your location and role.