Data Scientist

Job Description About the Role We are seeking a highly experienced Data Scientist with 5+ years of hands-on expertise to join our Analytics and AI team. The ideal candidate will have strong experience in building scalable data science solutions, advanced statistical modeling, and machine learning, along with the ability to translate complex data into actionable business insights. This role requires close collaboration with business stakeholders, engineering teams, and leadership to drive data-driven decision-making. Key Responsibilities Design, develop, and deploy end-to-end data science and machine learning solutions . Perform advanced data analysis, exploratory data analysis (EDA) , and feature engineering on large datasets. Build, train, tune, and optimize predictive, classification, clustering, and forecasting models . Analyze business datasets to identify trends, patterns, anomalies, and actionable insights . Collaborate closely with business stakeholders to translate analytical findings into data-driven strategies and recommendations . Work with data engineers to ensure scalable, reliable, and production-ready data pipelines . Utilize Databricks for large-scale data processing, collaborative analytics, and ML workflows. Work with Snowflake for cloud-based data warehousing, analytics, and optimized data access. Develop dashboards, reports, or analytical summaries to support leadership and operational decision-making when required. Communicate insights, model performance, risks, and recommendations to technical and non-technical audiences . Monitor model performance, manage data and model drift , and continuously improve deployed solutions. Mentor junior team members and contribute to data science standards, best practices, and reusable frameworks . Prepare and maintain technical documentation for models, methodologies, pipelines, and analytical insights. Required Skills & Qualifications Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics , or a related field. 5+ years of professional experience in data science, applied machine learning, or advanced analytics roles. Strong proficiency in Python (NumPy, Pandas, Scikit-learn, Statsmodels). Hands-on experience with machine learning algorithms (regression, classification, clustering, time series). Strong command of SQL for data extraction, transformation, and analysis. Solid understanding of statistics, probability, hypothesis testing, and experimental analysis . Proven experience performing EDA, data validation, and data quality checks on large datasets. Ability to derive business insights from data and present them clearly using visualizations. Experience with data visualization and reporting tools (Matplotlib, Seaborn, Plotly, Power BI, Tableau ). Working knowledge of Databricks for distributed data processing and ML workloads. Experience using Snowflake or similar cloud data warehouses for analytical querying and data modeling. Basic understanding of data warehousing concepts , dimensional modeling, and analytical data models. Strong analytical mindset, structured problem-solving skills, and excellent stakeholder communication abilities. Certifications (Preferred / Nice to Have) Databricks Certified Data Scientist / Machine Learning Professional Snowflake SnowPro Core or Advanced Certification AWS Certified Machine Learning – Specialty Google Professional Data Engineer Microsoft Azure Data Scientist Associate Any recognized Data Science, Machine Learning, or Cloud certification Good to Have Experience with deep learning frameworks (TensorFlow, PyTorch). Exposure to cloud platforms (AWS, GCP, Azure). Hands-on experience with big data technologies (Spark, Kafka, Hadoop). Knowledge of MLOps , CI/CD pipelines, model deployment, and monitoring. Experience working on business analytics, KPI tracking, or executive dashboards . Domain exposure in Finance, Retail, Healthcare, Manufacturing, or SaaS . Prior experience mentoring teams or leading data science initiatives .