Capgemini Engineering, the leader in engineering and R&D services, helps clients unleash their R&D potential.
Lead Data Scientist
Location
Mexico
Posted
70 days ago
Salary
0
Seniority
Lead
Job Description
Lead Data Scientist
Capgemini Engineering
RH: Lessly Mujica Location: any state of Mexico General Description: As a Lead Data Scientist, you will be at the forefront of our data science initiatives, leveraging advanced machine learning techniques and cloud technologies to deliver impactful solutions for our clients. You will lead the development and deployment of production-grade machine learning models using Azure's ecosystem, driving innovation and excellence in our data science practice. In this role you will play a key role in: - Leading the end-to-end machine learning lifecycle from problem formulation to production deployment, ensuring high-quality, scalable, and maintainable solutions - Architecting and implementing advanced ML pipelines using Azure ML, Databricks, and related services while adhering to best practices in MLOps - Developing and optimizing tabular machine learning models (XGBoost, LightGBM, Random Forest, Logistic Regression) with focus on explainability, performance tuning, fairness, and robustness - Building and maintaining scalable data processing pipelines using PySpark and Spark SQL to support model training and inference - Deploying models as REST APIs through Azure API Management and establishing monitoring frameworks for production models - Creating comprehensive documentation including model cards, validation reports, runbooks, lineage documentation, and operational guidelines - Leading cross-functional collaboration with platform teams, data engineers, governance specialists, and domain experts - Mentoring junior data scientists and establishing best practices for the team - Communicating complex technical concepts to stakeholders and influencing architectural decisions Your profile - Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or related technical field - 15+ years of overall IT experience with 6+ years delivering production-grade ML models using enterprise cloud platforms, including at least 3+ years in Azure ecosystems - Demonstrated expertise in Azure ML (workspaces, pipelines, model registry, endpoints), Azure Databricks (PySpark, Spark SQL, MLflow), Azure Data Factory (data pipelines & orchestration), Azure Data Lake (ADLS Gen2), and Azure DevOps CI/CD - Deep knowledge of tabular machine learning techniques including XGBoost, LightGBM, Random Forest, and Logistic Regression, with focus on explainability, performance tuning, fairness checks, and robustness validation - Strong Python development skills with experience building scalable data and ML pipelines using PySpark/Spark SQL - Experience working with Medallion Architecture (Bronze/Silver/Gold) and semantic layers - Proven ability to deploy models as REST APIs through API gateways or Azure API Management - Experience producing comprehensive documentation including model cards, validation reports, runbooks, lineage documentation, and operational guidelines - Familiarity with responsible AI practices, fairness testing, and SHAP explainability - Experience working in agile environments with SIT, UAT, and phased releases - Strong stakeholder management skills and ability to lead cross-functional collaboration - Experience in regulated domains (pharma, healthcare, clinical operations, CRO) is highly desirable - Knowledge of validation processes like GxP and CSV is a plus What you'll love about working here At Capgemini LATAM, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications welcome and will be considered based on merit against the job and/or experience for the position About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fuelled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
Related Guides
Related Categories
Related Job Pages
More Data Scientist Jobs
Senior Data Scientist
EXLWe make sense of data to drive your business forward. #MakeSenseofData #DriveYourBusinessForward #PartnerYourWay
Senior Data Scientists lead data analysis projects and provide strategic insights. Responsibilities include designing complex models, mentoring junior data scientists, and ensuring the quality of analytical work. You will work closely with business leaders to understand needs and deliver actionable insights. Extensive experience in data science and leadership skills are required.
• Perform complex data analyses and present the results to clients to help them interpret and action on the insights from the Recast model. • Onboard new clients onto Recast's platform, work hand-in-hand with them to set priors, interpret results, and plan experiments to validate the model. • Develop and manage data pipelines in R • Identify and enact process improvements to improve efficiency across the data science team
• Design and implement supervised and unsupervised ML models (e.g., OLS, Logistic Regression, Ensemble Methods) to solve real-world business problems. • Lead model development for advanced architectures in neural networks, such as ANN, CNN, RNN, GAN, Transformers, and RESNet. • Drive NLP advancements with tools like NLTK and neural-based language models. • Oversee the development of computer vision models, utilizing OpenCV for real-world applications. • Lead time-series modeling projects for forecasting and anomaly detection. • Utilize AI techniques like Retrieval-Augmented Generation (RAG), Chain of Thought (CoT), and Model of Alignment (MOA) to enhance model performance. • Build and maintain scalable data pipelines for both streaming and batch processing. • Architect and optimize lakehouse solutions using Delta/Iceberg and bronze-silver-gold architectures. • Lead the development of ETL processes with tools like Airflow, DBT, and Airbyte to support data flow and transformation. • Design and optimize database models for OLTP and OLAP systems using Snowflake, SQL Server, PostgreSQL, and MySQL. • Develop NoSQL solutions, leveraging MongoDB, DynamoDB, and ElasticSearch for unstructured data. • Lead efforts in building cloud infrastructure, particularly in AWS (preferred) or Azure, using services such as Lambda, API Gateway, Batch processing, Kinesis, and Kafka. • Oversee MLOps pipelines for robust deployment of ML models in production with platforms like Sagemaker, Databricks, and Azure ML Studio. • Develop and optimize business intelligence dashboards with tools like Tableau, QuickSight, and PowerBI for actionable insights. • Implement GPU acceleration and CUDA for model training and optimization. • Mentor junior team members in cutting-edge AI/ML techniques and best practices.
Role Description The Strategic Data Scientist will partner with operational, planning & procurement and finance partners to understand what is happening within the business so solutions can be developed to unlock strategic insights and then carry forward these insights to development of transformation plans that would be implemented (in working together with a project manager / operations leader). As a Strategic Data Scientist they will spend significant time developing strategic data insights to advance initiatives in efficiency, agility, cost optimization through customer-centric and operations-led settings. In addition, this role will partner with the purchasing & planning organization to develop insights to demand trends. - Undertakes research and analysis to evaluate consumer demand patterns, develop insights, work with executive team to undertake demand outlook analysis and determine inputs to purchasing plans so as to manage inventory and guide commercial & supply chain operations. - Focuses on leveraging data to optimize operations, improve efficiency, and drive business strategy through specific strategic projects. - Analyzes complex datasets to identify trends, patterns, and areas for improvement within the distribution network, and translate these findings into actionable insights and recommendations. - Develops / works with project management / operations leadership / commercial leadership to develop transformation plans and undertake change management. - Utilizes scenario modeling and predictive analytics to support strategic planning, conducts root cause analysis to support continuous improvement initiatives and monitors the effectiveness of implemented strategies and adjust based on performance data. Qualifications - 5 to 7 years of experience in Commercial & Strategic Finance, Supply Chain Finance, FP&A or related fields. - Bachelor's degree in Computer Science, Business, Data Analytics, Engineering, Finance, Economics, or equivalent experience required. - Prior experience working directly with one or more of the following domain areas – commercial & sales, supply chain or growth & transformation. - Experience creating dashboards and working in Power BI. - Bonus: Graduate degree in statistics, business, economics, econometrics, supply chain or related discipline. Requirements - Proficiency in statistical analytical software such as R, SAS, or SPSS, as well as database tools like SQL, MS Access, Excel PivotTables, and MS SQL Server. - Experience using and creating dashboards in visualization tools such as Python, Power BI, Tableau, and QlikView. - Expertise in MS Office suite, including Excel, Access, and PowerPoint. - Strong commitment to meeting deadlines and project schedules. - Present findings and actionable insights to both technical and non-technical stakeholders. - Support cross-functional teams with data-driven recommendations. - Comfortable analyzing data sets and working in data-sparse environments. - Excellent communication and presentation skills, including the ability to interact with senior executive management regularly. - Adaptability to change in a fast-paced and constantly evolving environment. - Effective project management skills. - Extreme attention to detail. - Highly motivated self-starter with a passion for making high quality analytical solutions. - Committed to a great user experience. - Strong sense of ownership and drive. - Positive, enthusiastic attitude with ability to interact with cross-departmental groups. Work Environment/Physical Demands - Typical office environment – moderate noise level. - This position regularly requires standing; walking; sitting; use hands; reaching with hands and arms; and talking and/or hearing. - Occasional lifting and/or moving up to 25 pounds. We are an equal opportunity employer, dedicated to fostering a diverse and inclusive workplace where everyone is valued and has equal access to opportunities. WE ARE A DRUG FREE WORKPLACE.
