Data Scientist

Job Title: Data Scientist

Job Summary

We are looking for a skilled Data Scientist who can extract meaningful insights from complex data, build predictive models, and drive data-informed decisions across the organization. The role involves collecting, processing, and analyzing large datasets, developing machine learning solutions, and communicating results to technical and non-technical stakeholders.

Key Responsibilities

Data Collection & Preparation

• Gather, clean, preprocess, and validate large structured and unstructured datasets from multiple sources.
• Ensure data quality, consistency, and accessibility for analysis.

Modeling & Analysis

• Develop, test, and deploy predictive models, machine learning algorithms, and statistical analyses to solve business problems. 
• Perform exploratory data analysis to identify trends, patterns, and actionable insights.

Visualization & Reporting

• Create dashboards, reports, and visualizations to present results clearly and effectively to stakeholders.
• Translate complex findings into business recommendations and storytelling.

Collaboration

• Work closely with cross-functional teams (product, engineering, finance, marketing) to understand data needs and integrate analytical solutions.
• Communicate insights and model results to both technical and non-technical audiences.

Model Deployment & Monitoring

• Collaborate with data engineers or ML engineers to operationalize models and monitor their performance in production.
• Ensure data science solutions are scalable, robust, and maintainable.

Continuous Learning

• Stay updated with emerging tools, techniques, and best practices in data science, AI/ML, and big data technologies. 

Required Qualifications

• Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Technical Skills:
  • Proficiency in programming languages such as Python, R, and SQL.
  • Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
  • Familiarity with data visualization tools/libraries (e.g., Tableau, Power BI, Matplotlib, Seaborn).

Preferred Skills

• Knowledge of big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud Platform).
• Experience with MLOps practices and deploying models to production.
• Background in domain-specific analytics (e.g., finance, healthcare, telecom) is a plus.