Data Science & Analytics Engineer
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Key skills for this role
About the Role
Datamatics Global Services is looking for a Data Science & Analytics Engineer with 3-11 years of experience to transform complex data into actionable business insights. The role requires expertise in data science, statistical analysis, predictive modeling, data visualization, and modern analytics platforms.
Key Skills for This Role
Responsibilities
- Design, develop, and deploy predictive and analytical models to solve business problems
- Perform data exploration, statistical analysis, feature engineering, and model evaluation
- Build interactive dashboards, reports, and visualizations for business stakeholders
- Develop scalable data analytics solutions using modern cloud and big data platforms
- Collaborate with cross functional teams to understand business requirements and translate them into analytical solutions
- Analyze structured and unstructured datasets to identify trends, patterns, and opportunities
- Ensure data quality, governance, and best practices across analytics initiatives
- Present analytical findings and recommendations to technical and non technical audiences
- Continuously improve analytics processes, reporting capabilities, and model performance
Requirements
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Information Technology, or related field
- 3 11 years of professional experience in Data Science, Business Analytics, or Advanced Analytics
- Strong proficiency in Python or R for data analysis, statistical modeling, and machine learning
- Hands on experience with Databricks or Dataiku for data science and machine learning
- Strong experience with Power BI, Tableau, or Looker for dashboard development and data visualization
- Experience with BigQuery or Snowflake for large scale analytics and data warehousing
- Strong understanding of SQL, data modeling, and analytical query optimization
- Experience with statistical analysis, forecasting, classification, clustering, and regression models
Full Job Posting
Job Overview
- We are looking for a talented Data Science & Analytics Engineer with 3–11 years of experience to transform complex data into actionable business insights.
- The ideal candidate will have expertise in data science, statistical analysis, predictive modeling, data visualization, and modern analytics platforms.
- You will work closely with business stakeholders, data engineers, and technology teams to develop data driven solutions that support strategic decision making.
Key Responsibilities
- Design, develop, and deploy predictive and analytical models to solve business problems.
- Perform data exploration, statistical analysis, feature engineering, and model evaluation.
- Build interactive dashboards, reports, and visualizations for business stakeholders.
- Develop scalable data analytics solutions using modern cloud and big data platforms.
- Collaborate with cross functional teams to understand business requirements and translate them into analytical solutions.
- Analyze structured and unstructured datasets to identify trends, patterns, and opportunities.
- Ensure data quality, governance, and best practices across analytics initiatives.
- Present analytical findings and recommendations to technical and non technical audiences.
- Continuously improve analytics processes, reporting capabilities, and model performance.
Required Technical Skills
- Programming & Data Science: Strong proficiency in Python or R for data analysis, statistical modeling, and machine learning.
- Data Science Platforms: Hands on experience with Databricks or Dataiku for data science, machine learning, and collaborative analytics.
- Business Intelligence & Visualization: Strong experience with Power BI, Tableau, or Looker for dashboard development and data visualization.
- Data Warehousing & Analytics: Experience with BigQuery or Snowflake for large scale analytics and data warehousing; strong understanding of SQL, data modeling, and analytical query optimization.
- Analytics & Machine Learning: Experience with statistical analysis, forecasting, classification, clustering, and regression models; familiarity with machine learning libraries and model evaluation techniques.
Qualifications
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Information Technology, or a related field.
- 3–11 years of professional experience in Data Science, Business Analytics, or Advanced Analytics.
- Strong analytical, mathematical, and problem solving skills.
- Excellent communication and presentation skills.
- Experience working in Agile/Scrum environments.
Preferred Skills
- Experience with cloud analytics platforms on AWS, Microsoft Azure, or Google Cloud Platform.
- Knowledge of MLOps, model deployment, and AI driven analytics.
- Experience with ETL/ELT processes and data engineering concepts.
- Familiarity with Generative AI, Large Language Models (LLMs), or AI assisted analytics is an advantage.
- Relevant certifications in Data Science, Analytics, or Cloud technologies are a plus.
Key Technology Stack
- Programming Languages: Python or R
- Data Science Platforms: Databricks or Dataiku
- Business Intelligence: Power BI, Tableau, or Looker
- Data Warehouse: BigQuery or Snowflake
- Analytics: Statistical Analysis, Predictive Modeling, Machine Learning, Data Visualization
- Cloud Platforms: AWS, Microsoft Azure, or Google Cloud Platform (Preferred)
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