Key Responsibilities:
- Collect, clean, preprocess, and analyze large datasets.
- Develop and implement machine learning and statistical models.
- Identify trends, patterns, and actionable insights from data.
- Perform exploratory data analysis (EDA) and feature engineering.
- Build, evaluate, and optimize predictive models.
- Work with structured and unstructured data.
- Create dashboards and visualizations to communicate insights.
- Collaborate with business teams, data engineers, and software developers.
- Monitor model performance and improve models when required.
- Present findings and recommendations to technical and non-technical stakeholders.
- Maintain documentation for data analysis, models, and methodologies.
Required Skills:
- Strong knowledge of Python or R.
- Good understanding of statistics, probability, and machine learning.
- Experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Strong SQL and database knowledge.
- Experience with data visualization tools such as Power BI, Tableau, or Matplotlib.
- Knowledge of supervised and unsupervised learning techniques.
- Understanding of data preprocessing, feature engineering, and model evaluation.
- Strong analytical and problem-solving skills.