Tiger Analytics - Data Scientist

About the Role:
We are looking for a talented Data Scientist with 4+ years of experience to develop data-driven solutions that solve complex business problems. The ideal candidate should have strong expertise in Machine Learning, Statistical Modeling, Python, SQL, and Data Analytics, with experience in building predictive models, extracting actionable insights, and deploying scalable machine learning solutions.
You will work closely with business stakeholders, data engineers, and product teams to leverage data for strategic decision-making and business growth.
Key Responsibilities :
- Collect, clean, preprocess, and analyze large structured and unstructured datasets.
- Design, build, and deploy machine learning models for predictive analytics and business optimization.
- Perform exploratory data analysis (EDA) to identify trends, patterns, and business opportunities.

- Develop statistical models and predictive algorithms to solve real-world business problems.
- Build and optimize data pipelines in collaboration with Data Engineering teams.
- Evaluate model performance and continuously improve model accuracy and efficiency.
- Create dashboards, reports, and visualizations to communicate analytical insights to stakeholders.
- Conduct A/B testing and hypothesis testing to support product and business decisions.
- Deploy machine learning models into production environments and monitor their performance.
- Collaborate with cross-functional teams to translate business requirements into analytical solutions.
- Stay updated with emerging technologies and advancements in AI, Machine Learning, and Data Science.
Required Skills:
- Strong proficiency in Python for data analysis and machine learning.
- Excellent knowledge of SQL and database querying.
- Hands-on experience with Machine Learning algorithms and statistical modeling.
- Experience with libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, PyTorch, or XGBoost.
- Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Experience with data visualization tools such as Power BI, Tableau, Matplotlib, or Plotly.
- Knowledge of predictive analytics, regression, classification, clustering, and time-series forecasting.
- Experience working with cloud platforms such as AWS, Azure, or GCP is an advantage.
- Strong analytical, problem-solving, and critical-thinking skills.