Position Overview:
We are seeking a talented and experienced Mid-Level Data Scientist to join our data analytics team. As a Data Scientist, you will be responsible for applying advanced data analysis techniques and statistical modeling to extract meaningful insights from complex datasets. You will work on various data-driven projects, contributing to the development of predictive models, machine learning algorithms, and data-driven solutions to support business decision-making.
Responsibilities:
- Collect, clean, and preprocess large and diverse datasets from various sources to ensure data quality and consistency. Perform exploratory data analysis to understand data patterns and identify relevant features for modeling.
- Develop and implement machine learning algorithms and predictive models to solve business problems and extract valuable insights.Utilize a wide range of techniques such as regression, classification, clustering, and deep learning as per project requirements.
- Evaluate the performance of machine learning models using appropriate metrics, validating their effectiveness, and fine-tuning hyperparameters.Apply cross-validation techniques to assess model generalization and mitigate overfitting.
- Communicate complex data insights to non-technical stakeholders through data visualizations and easy-to-understand reports.Generate visualizations and dashboards to track key performance indicators and monitor model performance
- Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to define project objectives and scope.Provide data science expertise and insights to support data-related projects across the organization.
Eligibility & Requirement:
- Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
- Proven experience as a Data Scientist or related role, preferably 3+ years of industry experience.
- Strong programming skills in languages such as Python or R, with experience in data manipulation libraries (e.g., Pandas, NumPy).
- Proficiency in machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
- Solid understanding of statistical concepts and methodologies.
- Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) to communicate results effectively.
- Excellent communication skills to explain technical concepts to non-technical audiences.
