Senior Data Scientist

Marsh & McLennan Companies; Ciudad de México; Híbrido; MXN 70,000 - 100,000; Jornada completa

Descripción de la vacante

A leading global advisory firm is seeking a Senior Data Scientist in Mexico City. The role involves analyzing complex datasets, building machine learning models, and developing automated data pipelines. Candidates should have a degree in a quantitative field and at least 4 years of experience with cloud technologies and Python programming. Join a vibrant culture that fosters professional development and inclusion, with a hybrid work model requiring presence in the office three days a week.

Servicios

Professional development opportunities

Supportive work culture

Flexible work schedule

Formación

• 4+ years of experience with cloud‑based data science and engineering technologies.
• Proficient in SQL and experienced with database management.
• Strong programming skills in Python.

Responsabilidades

• Analyze complex datasets and build scalable machine learning models.
• Design and implement efficient code for data manipulation and model development.
• Develop and maintain automated ETL pipelines leveraging cloud platforms.

Conocimientos

Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch)

SQL

Data Visualization (Power BI, Tableau)

Problem-solving

Strong analytical skills

Educación

Bachelor’s or master’s degree in computer science, Data Science, Statistics, Mathematics

Herramientas

Databricks

AWS S3

Redshift

Snowflake

Azure Synapse

Descripción del empleo

Company: Oliver Wyman Description:

Senior Data Scientist

We are seeking a Senior Data Scientist to join our team at Marsh. This role will be based in Mexico City. This is a hybrid role that has a requirement of working at least three days a week in the office. As a Senior Data Scientist at Marsh, you will analyze complex datasets, build scalable machine learning models, and develop automated data pipelines to drive data-driven decision-making across the organization. This role requires strong technical expertise, business acumen, and the ability to work within enterprise environments adhering to data governance, security, and compliance standards.

We will count on you to:

• Partner with business groups and technology teams to understand strategic objectives and translate them into actionable data science projects aligned with enterprise goals.
• Design, develop, and implement efficient, scalable, and maintainable code for data manipulation and machine learning model development using Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) or R.
• Develop and maintain automated ETL pipelines leveraging cloud-based platforms such as Databricks, AWS S3, Athena, Glue, or equivalent enterprise data platforms.
• Utilize GenAI and ChatGPT APIs to automate data ingestion and processing workflows; familiarity with large language models (LLM), retrieval-augmented generation (RAG), Power BI, and Tableau is a plus.
• Create and maintain automation scripts for data extraction, transformation, and reporting using Python and other scripting languages.
• Write optimized SQL queries and manage enterprise-grade database systems; experience with data warehousing solutions such as Redshift, Snowflake, or Azure Synapse is required.
• Demonstrate expertise in data modeling, transformation, storytelling, and visualization using Power BI, Tableau, or similar BI tools.
• Apply machine learning, statistical modeling, and time-series forecasting techniques (classification, regression, clustering, random forest, gradient boosting, etc.) to build, calibrate, and validate predictive models.
• Deliver end-to-end data pipelines and deploy machine learning models in production environments following enterprise best practices for scalability, monitoring, and governance.
• Ensure compliance with data privacy, security policies, and regulatory requirements (e.g., GDPR, HIPAA) during data handling and model deployment.

What you need to have:

• Bachelor’s or master’s degree in computer science, Data Science, Statistics, Mathematics, or a related quantitative field.
• 4+ years of hands‑on experience with cloud‑based data science and engineering technologies, including platforms like Databricks, AWS S3, Athena, Glue, or comparable enterprise cloud services.
• Strong programming skills in Python with expertise in libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Proficient in SQL and experienced with enterprise database management and data warehousing technologies (e.g., Databricks, Redshift, Snowflake or Azure Synapse).
• Experience designing and developing automated data pipelines and workflows; familiarity with Git, CI/CD, and DevOps principles.
• Proven ability to design, implement, and deploy machine learning models and data workflows in production environments.
• Strong analytical, problem‑solving, and communication skills, with the ability to translate complex technical concepts for diverse audiences.
• Advanced Level of English is a Must

What makes you stand out:

• Experience with GenAI, ChatGPT API integration, and working knowledge of large language models (LLM) and retrieval-augmented generation (RAG).
• Proficiency in data visualization tools such as Power BI, Tableau, or equivalent.
• Familiarity with REST API development and integration.

Why join our team:

• We help you be your best through professional development opportunities, interesting work and supportive leaders.
• We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
• Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well‑being.

Marsh McLennan (NYSE: MMC) is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit marshmclennan.com, or follow on LinkedIn and X. Marsh McLennan is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.