Data Science & Analytics Engineer
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Key skills for this role
About the Role
Datamatics Technologies is hiring a Data Science & Analytics Engineer with 3-11 years of experience to transform complex data into actionable business insights. The role involves designing predictive models, building dashboards, and collaborating with cross-functional teams.
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
- 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 or 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
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Information Technology, or related field
Full Job Posting
Job Overview
- Looking for a talented Data Science & Analytics Engineer with 3–11 years of experience.
- Transform complex data into actionable business insights.
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
- Strong proficiency in Python or R for data analysis, statistical modeling, and machine learning.
- Hands on experience with Databricks or Dataiku for data science, machine learning, and collaborative analytics.
- Strong experience with Power BI or 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.
- 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 or Tableau or Looker
- Data Warehouse: BigQuery or Snowflake
- Analytics: Statistical Analysis and Predictive Modeling and Machine Learning and Data Visualization
- Cloud Platforms: AWS or Microsoft Azure or Google Cloud Platform (Preferred)
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