Data Scientist

Summary:

We are looking for a skilled professional to join our team and support the broader data and analytics organization. The ideal candidate will have a strong foundation in statistics, data modeling, and data science, along with practical experience in data engineering and data preparation. This role will work closely with cross-functional teams to analyze complex datasets, develop statistical and predictive models, generate actionable insights, and help build reliable data pipelines and solutions. The successful candidate should be comfortable working across both the analytical and technical aspects of data science.

• Client is looking for senior, independent professionals, not execution-focused resources.
• Strong critical thinking and problem-solving skills are essential.
• Candidates should be comfortable working with ambiguous requirements and defining the approach independently.
• Must have strong business stakeholder communication and collaboration skills.
• Should be capable of owning projects end to end.
• Strong initiative, accountability, and decision-making skills are key expectations.
• Client is not primarily looking for routine SQL/coding-focused professionals.
• Prioritize candidates who can understand business problems, identify solutions, and independently drive them through completion.

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.

Requirements:

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related field.
• 5 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 Skills:

• 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.

Benefits:

Details about benefits will be provided during the interview process.