Jobs → Data & Analytics → Data Scientist

About the Role We are seeking an experienced Data Scientist to analyze complex datasets, develop machine learning models, and deliver data-driven insights that support business decisions. The ideal candidate will have strong expertise in Python, SQL, statistics, machine learning, data visualization, and predictive analytics, with experience working across the complete data science lifecycle. Key Responsibilities • Analyze large and complex datasets to identify trends, patterns, and business opportunities. • Develop, train, validate, and deploy machine learning and statistical models. • Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis. • Apply supervised and unsupervised learning techniques to solve business problems. • Build predictive models for forecasting, classification, regression, recommendation, and anomaly detection. • Evaluate model performance using appropriate statistical and machine learning metrics. • Create dashboards, reports, and visualizations to communicate analytical findings. • Collaborate with data engineers to develop scalable data pipelines and analytical datasets. • Work with business stakeholders to understand requirements and translate them into analytical solutions. • Perform statistical analysis, hypothesis testing, experimentation, and A/B testing. • Deploy models into production and monitor model performance and data quality. • Optimize existing models and analytical processes for accuracy, scalability, and performance. • Document methodologies, assumptions, models, and analytical results. • Research emerging machine learning, AI, and data science technologies. Requirements • 4+ years of experience in Data Science, Machine Learning, or a related field. • Strong programming skills in Python. • Strong knowledge of statistics, probability, and machine learning concepts. • Hands-on experience with Pandas, NumPy, Scikit-learn, and SciPy. • Experience with machine learning algorithms including regression, classification, clustering, and ensemble methods. • Strong SQL skills and experience working with relational databases. • Experience with data visualization tools such as Power BI, Tableau, Matplotlib, or Seaborn. • Experience with model evaluation, feature engineering, and optimization. • Knowledge of ML deployment and MLOps practices. • Strong analytical, problem-solving, and communication skills.