Data Scientist - Consumer Analytics, Forecasting
J
JobgetherData Science
IndiaFull-Time
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLGCPMachine LearningAzureDatabricks
Requirements
- Commercial experience applying classical data science and machine learning models, including decision trees, ensemble-based models, and linear regression.
- Strong understanding of consumer analytics concepts and advanced forecasting techniques.
- Experience with hyperparameter tuning and model validation frameworks.
- Ability to gather business requirements, design technical solutions, process data, engineer features, and evaluate models.
- Experience supporting business teams through analytical insights and data-driven recommendations.
- Strong programming skills in Python and basic working knowledge of SQL.
- Familiarity with data science and machine learning libraries.
- Experience working with cloud computing platforms such as Databricks, GCP, or Azure.
- Strong analytical thinking and ability to solve complex business problems creatively.
- Good understanding of programming concepts and software development practices.
Responsibilities
- Manage end-to-end data science initiatives, including business understanding, data preparation, modeling, evaluation, and deployment.
- Analyze complex datasets and interpret findings to identify meaningful business insights.
- Develop predictive models and forecasting solutions to support business planning and operational improvements.
- Translate analytical outcomes into clear recommendations, including expected business benefits and ROI measurement.
- Gather business requirements and convert them into technical plans, analytical approaches, and implementation strategies.
- Perform feature engineering, model evaluation, and optimization to improve model performance.
- Apply machine learning techniques such as decision trees, ensemble models, regression, and other classical ML approaches.
- Support pre-sales activities by contributing technical expertise and presenting data science solutions to stakeholders.
- Collaborate with cross-functional teams to understand customer challenges and develop creative analytical solutions.
- Contribute to best practices in data science methodologies, model validation, and deployment processes.
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