Data Scientist

Description

Job Summary: Design and develop statistical and machine learning models to solve complex problems, lead end-to-end applied research projects, and collaborate with multidisciplinary teams. Key Highlights: 1. Statistical and machine learning model design and development 2. End-to-end leadership of applied research projects 3. Collaboration with multidisciplinary teams to integrate models INFORMATION SENIOR CONSULTANT 5 hours ago Description Design and develop statistical and machine learning models to solve complex problems in scientific and business environments. Analytical, problem-solving oriented, and critically thinking. Ability to communicate technical findings to non-technical audiences. Proactive, with strong leadership skills for research and development projects. Focus on generating scientific knowledge and reproducible methodologies. Requirements Academic Qualifications: * Bachelor’s or graduate degree (Master’s or Ph.D.) in fields focused on scientific research, such as Physics, Mathematics, Actuarial Science, Statistics, Computer Science, or related disciplines. Technical Requirements: * Experience in academic or applied research projects, preferably with publications in peer-reviewed scientific journals or reputable conferences. * Professional Experience: More than 5 years of experience in data science, statistical analysis, or applied research roles. * Experience leading end-to-end data science projects, from problem definition to solution implementation. * Experience working with large-scale datasets and distributed computing environments. * Experience applying advanced modeling techniques, such as deep neural networks, Bayesian models, time series analysis, and mathematical optimization. * Programming Languages: Python (advanced), R, Julia. * Data Science and ML Libraries: NumPy, Pandas, Scikit\-Learn, TensorFlow, PyTorch, Statsmodels, XGBoost, LightGBM. * Statistical Analysis and Modeling: SPSS, SAS, MATLAB. * Data Visualization: Matplotlib, Seaborn, Plotly, Tableau, Power BI. * Big Data and Distributed Processing: Spark, Dask, Hadoop. * Databases: SQL, NoSQL (MongoDB, Cassandra), PostgreSQL. * ETL and Orchestration: Apache Airflow, Luigi. * Infrastructure and MLOps: Docker, Kubernetes, MLflow, Kubeflow. * Cloud Computing: AWS, GCP, Azure. Additional Qualifications: * Advanced knowledge of inferential statistics, experimental design, and hypothesis testing. * Experience in scientific research and publication of articles in academic journals. * Familiarity with agile methodologies and project management (Scrum, Kanban). * Knowledge in bioinformatics, econometrics, or other domain-specific scientific applications (optional). * Recommended Academic Background and Experience: Responsibilities: * Design and develop statistical and machine learning models to solve complex problems in scientific and business environments. * Perform exploratory data analysis (EDA) to identify patterns, trends, and significant relationships. * Lead applied research projects, from hypothesis formulation to result validation. * Collaborate with multidisciplinary teams to integrate predictive models into products and services. * Implement reproducible data and model pipelines, ensuring traceability and result quality. * Develop and apply advanced modeling techniques, such as deep neural networks, Bayesian models, and time series analysis. * Document and communicate key findings in technical reports and scientific publications. * Design validation and monitoring strategies to ensure model robustness and performance in production. * Identify opportunities for scientific innovation through data and emerging technologies. * Propose data-driven solutions to specific business or research problems, aligned with the organization’s strategic objectives. Profile **SENIOR CONSULTANT** Location **Huixquilucan, State of Mexico, Mexico (Hybrid)**Experience **3 Years of Experience** o