Job Summary
We are looking for a skilled and business-oriented Data Scientist to join our data team. The ideal candidate should have strong experience in Python, machine learning models, statistical analysis, and working with different types of databases. This role requires someone who can not only build analytical and predictive models, but also translate data into clear, actionable business insights that support decision-making across the organization.

Key Responsibilities
Analyze large and complex datasets to identify patterns, trends, and business opportunities.
Build, train, evaluate, and improve machine learning models for prediction, classification, clustering, forecasting, and optimization problems.
Use Python and relevant data science libraries such as Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, or PyTorch.
Work with structured and unstructured data from different sources and databases.
Generate meaningful business insights and present findings clearly to technical and non-technical stakeholders.
Collaborate with product, business, operations, and data engineering teams to define analytical requirements and solve business problems.
Design and monitor key metrics, dashboards, and reports to track business performance.
Perform data cleaning, feature engineering, exploratory data analysis, and model validation.
Support data-driven decision-making by providing recommendations based on analysis and model outputs.
Work with SQL and different database technologies such as SQL Server, PostgreSQL, MySQL, MongoDB, ClickHouse, or other analytical databases.
Communicate results through clear visualizations, reports, and presentations.
Stay updated with new data science methods, machine learning techniques, and industry best practices.

Required Skills and Qualifications
Strong programming skills in Python.
Good understanding of machine learning algorithms and model evaluation techniques.
Experience with data analysis, statistical modeling, and feature engineering.
Strong SQL skills and experience working with different database systems.
Ability to work with large datasets and complex business data.
Experience with data visualization tools and libraries such as Matplotlib, Seaborn, Plotly, Power BI, or Tableau.
Strong problem-solving and analytical thinking skills.
Ability to translate business questions into data science solutions.
Good communication skills and the ability to explain technical concepts to business teams.
Experience with model deployment, APIs, or MLOps is a plus (optional).
Experience in logistics, e-commerce, fintech, retail, or customer behavior analysis is a plus.

Preferred Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
Experience with forecasting, recommendation systems, customer segmentation, fraud detection, pricing models, or operational optimization.
Familiarity with cloud platforms, data pipelines, and big data tools is an advantage.

What We Expect
We are looking for someone who can go beyond technical modeling and provide real business value. The ideal candidate should be curious, detail-oriented, and able to connect data insights with business impact.