Description

Key Responsibilities

·         Analyze large and complex datasets to identify trends, patterns, relationships, and actionable business insights.

·         Apply statistical methods and data science techniques to solve business and technical problems.

·         Develop, validate, and deploy predictive, statistical, and machine learning models.

·         Perform exploratory data analysis, feature engineering, data transformation, and data validation.

·         Partner with data engineers and other technical teams to develop and maintain data pipelines and datasets required for analytics and modeling.

·         Work with structured and unstructured data from multiple sources.

·         Support data ingestion, cleansing, transformation, and integration activities.

·         Translate business requirements and analytical questions into data-driven solutions.

·         Collaborate with the broader data science, engineering, product, and business teams.

·         Communicate analytical findings, model results, and recommendations clearly to both technical and non-technical stakeholders.

·         Monitor model performance and data quality and continuously improve analytical solutions.

·         Contribute to data science best practices, reusable frameworks, documentation, and technical standards.

Required Qualifications

·         Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related field.

·         15+ years of professional experience in Data Science, Statistical Modeling, Machine Learning, or related analytical roles.

·         Strong hands-on experience in statistics, statistical modeling, and data science.

·         Strong proficiency in Python and/or R for data analysis, modeling, and machine learning.

·         Strong SQL skills and experience working with relational databases.

·         Hands-on experience with data preparation, transformation, feature engineering, and data validation.

·         Working knowledge of data engineering concepts, including ETL/ELT, data pipelines, data integration, and data quality.

·         Experience working with large and complex datasets from multiple data sources.

·         Strong analytical and problem-solving skills.

·         Ability to independently translate analytical/business requirements into data-driven solutions.

·         Strong communication and presentation skills, with the ability to work effectively with technical and non-technical stakeholders.

·         Ability to work effectively with distributed/nearshore teams and maintain required client time-zone overlap.

Preferred Qualifications

·         Experience with cloud data platforms such as AWS, Azure, or Google Cloud.

·         Experience with data engineering tools and frameworks such as Spark, Databricks, Airflow, or similar technologies.

·         Experience working with modern data warehouses/lakehouses.

·         Familiarity with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.

·         Experience with data visualization tools such as Tableau, Power BI, or similar platforms.

·         Knowledge of experimentation, A/B testing, forecasting, optimization, or time-series analysis.

·         Experience working in an Agile or cross-functional environment

Key Skills

Education

Bachelor's degree