Data Scientist

Description :

We are seeking a highly analytical and innovative Data Scientist to join our team.

The ideal candidate will be responsible for analyzing complex datasets, building predictive models, generating actionable insights, and supporting data-driven decision-making across business functions.

The role requires strong expertise in statistics, machine learning, data analysis, and programming, along with the ability to solve real-world business problems using advanced analytics techniques.

Key Responsibilities :

- Collect, clean, process, and analyze structured and unstructured data from multiple sources.

- Develop predictive models, machine learning algorithms, and statistical solutions to solve business challenges.

- Perform exploratory data analysis (EDA) to identify trends, patterns, and insights.

- Build and optimize classification, regression, clustering, forecasting, and recommendation models.

- Collaborate with business stakeholders to understand objectives and translate them into analytical solutions.

- Develop data pipelines, feature engineering processes, and model evaluation frameworks.

- Deploy and monitor machine learning models in production environments.

- Create dashboards, visualizations, and reports to communicate findings and recommendations effectively.

- Work with large datasets using SQL, Python, R, or big data technologies.

- Evaluate model performance, accuracy, scalability, and business impact.

- Stay updated with emerging trends in AI, machine learning, and data science technologies.

- Ensure data quality, governance, security, and compliance standards are maintained.

Required Skills & Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field.

- 3 to 8 years of experience in Data Science, Machine Learning, or Advanced Analytics.

- Strong proficiency in Python or R for data analysis and machine learning.

- Experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar frameworks.

- Strong knowledge of statistics, probability, and predictive modeling techniques.

- Expertise in SQL and database querying.

- Experience with data visualization tools such as Tableau, Power BI, Matplotlib, or Plotly.

- Knowledge of feature engineering, model tuning, and evaluation methodologies.

- Familiarity with cloud platforms such as AWS, Azure, or GCP.

- Experience working with large-scale datasets and distributed data processing frameworks is a plus.

- Strong analytical, problem-solving, and communication skills