Data Science & Analytics Engineer
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Data Science & Analytics Engineer
Location
Karachi, Sindh, Pakistan
Experience
Mid
Posted
Jul 10, 2026
Apply by
August 9, 2026
Applicants
0
Early applicantFull-timeHybrid
Job Description
# Job Description: Data Science & Analytics Engineer
**Job Title:** Data Science & Analytics Engineer
**Experience:** 3–11 Years
**Location:** Islamabad (On-site/Hybrid as per business requirement)
**Employment Type:** Full-Time
## 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.
- Experience with data manipulation, exploratory data analysis (EDA), and predictive analytics.
### Data Science Platforms
- Hands-on experience with **Databricks or Dataiku** for data science, machine learning, and collaborative analytics.
- Experience developing end-to-end analytical workflows and model deployment.
### Business Intelligence & Visualization
- Strong experience with **Power BI or Tableau or Looker** for dashboard development and data visualization.
- Ability to create interactive reports and executive-level dashboards.
### 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 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)
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.
Requirements
- Bachelor's degree in Data Science
- Computer Science
- Statistics
- Mathematics
- Information Technology
- or a related field
Skills Required
PythonRDatabricksDataikuPower BITableauLookerBigQuerySnowflakeSQLData ModelingStatistical AnalysisPredictive ModelingMachine LearningData VisualizationAgileScrumAnalytical skillsMathematical skillsProblem-solving skillsCommunication skillsPresentation skillsAWSMicrosoft AzureGoogle Cloud PlatformMLOpsETL/ELTGenerative AILarge Language Models (LLMs)AI-assisted analytics
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