Data Scientist_5+ years

We are seeking a highly motivated and experienced Data Scientist to join our growing team. The ideal candidate will have strong expertise in machine learning, statistical modeling, data engineering, and cloud-based AI/ML solutions. You will work closely with business stakeholders, engineering teams, and data professionals to develop scalable machine learning products and data-driven solutions that drive business impact. Key Responsibilities Perform Exploratory Data Analysis (EDA) to identify trends, patterns, and actionable insights from large datasets.Design, build, and optimize machine learning models for various business use cases.Develop and maintain feature engineering pipelines, feature selection frameworks, and online/offline feature stores.Build and manage batch and real-time streaming data pipelines using modern data platforms.Collaborate with business, engineering, infrastructure, and data science teams to translate business challenges into AI/ML solutions.Deploy, monitor, and maintain machine learning models in production environments.Develop reusable ML components, libraries, CI/CD pipelines, deployment standards, and technical documentation.Evaluate model performance using appropriate statistical and machine learning metrics.Create compelling visualizations, dashboards, and presentations to communicate findings and recommendations to technical and non-technical stakeholders.Support the full machine learning lifecycle, from data collection and experimentation to deployment and monitoring. Required Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.4+ years of experience in Data Science, Machine Learning, or Applied AI.Strong proficiency in Python and SQL.Experience with Git and software development best practices.Hands-on experience with Databricks, PySpark, and Apache Spark.Strong understanding of machine learning algorithms, statistical analysis, and model evaluation techniques.Experience building and deploying machine learning solutions in Azure Cloud environments.Knowledge of MLOps practices, CI/CD pipelines, and model lifecycle management.Experience working with large-scale structured and unstructured datasets. Preferred Qualifications Experience in one or more of the following areas: Time Series ForecastingRecommendation SystemsA/B Testing and ExperimentationDynamic PricingLogistics and Supply Chain OptimizationChurn PredictionCustomer SegmentationNatural Language Processing (NLP)Deep LearningReinforcement Learning Technical SkillsProgramming & Data PythonSQLPySparkApache SparkGit Cloud & Infrastructure Microsoft AzureKubernetesDocker Machine Learning & AI Scikit-learnPyTorchTensorFlowKerasMLOps Frameworks Data Platforms DatabricksFeature StoresReal-Time Streaming Architectures What You'll Bring Strong analytical and problem-solving skills.Ability to work in a fast-paced, collaborative environment.Excellent communication and stakeholder management skills.Experience presenting technical concepts and analytical findings to diverse audiences.Passion for building scalable AI/ML solutions that deliver measurable business value. Interview Process Candidates Should Be Prepared To Demonstrate Proficiency In Statistics and ProbabilityMachine LearningPython ProgrammingSQLPySparkOptimization TechniquesMLOps and Model DeploymentTechnical Coding Assessments and Take-Home Assignments Skills: python,pyspark,machine learning,sql We are seeking a highly motivated and experienced Data Scientist to join our growing team. The ideal candidate will have strong expertise in machine learning, statistical modeling, data engineering, and cloud-based AI/ML solutions. You will work closely with business stakeholders, engineering teams, and data professionals to develop scalable machine learning products and data-driven solutions that drive business impact. Key Responsibilities Perform Exploratory Data Analysis (EDA) to identify trends, patterns, and actionable insights from large datasets.Design, build, and optimize machine learning models for various business use cases.Develop and maintain feature engineering pipelines, feature selection frameworks, and online/offline feature stores.Build and manage batch and real-time streaming data pipelines using modern data platforms.Collaborate with business, engineering, infrastructure, and data science teams to translate business challenges into AI/ML solutions.Deploy, monitor, and maintain machine learning models in production environments.Develop reusable ML components, libraries, CI/CD pipelines, deployment standards, and technical documentation.Evaluate model performance using appropriate statistical and machine learning metrics.Create compelling visualizations, dashboards, and presentations to communicate findings and recommendations to technical and non-technical stakeholders.Support the full machine learning lifecycle, from data collection and experimentatio