Data Scientist
Summary
Data Scientist analyzing large datasets, building and deploying ML models (forecasting, classification, clustering, anomaly detection), and collaborating with stakeholders using Python, SQL, and cloud platforms.
We are searching for a talented and experienced Data Scientist to join our team and contribute to our data-centric initiatives. The successful candidate will play a pivotal role in analyzing large datasets, designing machine learning models, and collaborating with stakeholders to deliver innovative solutions. This role offers an opportunity to work with cutting-edge technologies and have a direct impact on our business strategies.
- Analyze complex datasets to identify trends and patterns, uncovering business opportunities.
- Design, develop, and deploy machine learning models, ensuring their validation and optimization.
- Build efficient data pipelines for data preparation, feature engineering, and model training.
- Perform exploratory data analysis and statistical techniques to derive meaningful insights.
- Develop a range of models including forecasting, classification, clustering, and anomaly detection.
- Collaborate closely with business stakeholders to understand their requirements and translate them into analytical solutions.
- Communicate findings and recommendations through comprehensive reports, dashboards, and presentations.
- Monitor model performance and implement necessary improvements to enhance accuracy and efficiency.
- Work in tandem with Data Engineers, BI Developers, and Product Owners to ensure seamless integration of data-driven solutions.
- Adhere to data governance, security, and compliance standards throughout the data science lifecycle.
- 3-6 years of hands-on experience in Data Science or Machine Learning, demonstrating a strong track record.
- Proficiency in Python, particularly with libraries like Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch.
- Experience with SQL and data manipulation across structured and unstructured datasets is essential.
- A solid understanding of statistical concepts, probability theory, hypothesis testing, and predictive analytics.
- Proven ability to build and deploy machine learning models in production environments, ensuring scalability.
- Knowledge of supervised and unsupervised learning techniques, along with experience in feature engineering and model evaluation.
- Familiarity with data visualization tools such as Power BI, Tableau, or Matplotlib for effective communication of insights.
- Experience working with cloud platforms like Azure, AWS, or GCP, leveraging their services for data processing and storage.
- Strong analytical and problem-solving skills, coupled with excellent communication abilities, both written and verbal.
- A Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.