Data Engineer

Job Title:

Location:

Job Summary

Data Scientist

Key Responsibilities

• Data Collection & Processing

• Gather data from multiple internal and external sources.
• Perform data cleaning, validation, and transformation for analysis.

• Exploratory Data Analysis (EDA)

• Identify patterns, anomalies, and trends within large datasets.
• Communicate findings through compelling data visualizations.

• Model Development & Deployment

• Develop predictive, prescriptive, and descriptive models using machine learning and statistical methods.
• Test and validate models for accuracy, performance, and scalability.
• Deploy models into production environments and monitor their performance over time.

• Business Insight & Decision Support

• Translate complex analytical results into clear, actionable insights for stakeholders.
• Partner with product, engineering, and business teams to identify opportunities for leveraging data.

• Tooling & Automation

• Build and maintain data pipelines for analysis and reporting.
• Automate repetitive data processes to improve efficiency.

• Research & Innovation

• Stay up to date with advancements in data science, AI, and analytics tools.
• Experiment with new algorithms, methodologies, and technologies.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related field.
• 2+ years of experience in data science, analytics, or machine learning roles (for mid-level positions).

Technical Skills

• Strong proficiency in

  Python

  or

  R

  for data analysis and modeling.
• Experience with

  SQL

  and relational databases.
• Familiarity with big data frameworks (e.g., Spark, Hadoop) is a plus.
• Knowledge of data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn, Plotly).
• Solid understanding of machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong grasp of statistics, probability, and hypothesis testing.

Soft Skills

• Excellent problem-solving and critical thinking skills.
• Ability to clearly communicate technical findings to non-technical stakeholders.
• Strong collaboration skills in cross-functional teams.

Preferred Qualifications

• Experience working with cloud platforms (AWS, Azure, GCP).
• Exposure to MLOps practices for model lifecycle management.
• Domain knowledge in [industry: e.g., finance, e-commerce, healthcare].

What We Offer

• Competitive salary and performance-based bonuses.
• Flexible working hours and remote work options.
• Professional development opportunities, including training and certifications.
• Collaborative, innovative, and data-driven work culture.