Data Analyst with AI/ML and Databricks

Position : Data Analyst with AI/ML and databricks Location : New York City (no relocation candidates) Work Visa : H4 EAD. Green Card EAD. GC, US Citizen Only Pay: $55 On W2 Work Mode : Hybrid 3 days onsite and 2 day Remote Interview : Onsite Interview (Mandatory ) JOB SUMMARY Designing and maintaining data • Azure Databricks required & ML/AI JOB DESCRIPTION • Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field. • Strong experience in machine learning algorithms, predictive modeling, and data mining. • Proficiency in Pyspark, Python pandas (required) for data science workloads. • Strong SQL (required) knowledge and experience with relational databases. • Minimum 3 years of experience with data visualization tools such as Power BI, Dax Queries, and best practices. • Experience with Azure Databricks, Google Cloud, and modern data science libraries (e.g., scikit-learn, pandas, NumPy). • Experience with GenAI and large language models. • Ability to interpret complex datasets and produce actionable insights. • Must know how to analyze the root cause of dashboard errors. • Have experience in ML Ops and have strong coding background. • Have experience with Natural Language Processing (NLP). • Knowledge or experience with A/B Testing. • Working knowledge of designing, training, and implementing machine learning models. • Familiarity with cloud-based infrastructure • Excellent communication and problem-solving skills. • 7 or more years of experience in data science and machine learning engineering. Additional Skills (Skills that are a plus, but not required) • Knowledge of statistical methods and experimental design. Responsibilities • Key Responsibilities Advanced Analytics & Machine Learning • Design, develop, and optimize machine learning models (forecasting, classification, clustering). • Apply data mining techniques to uncover patterns and insights in large datasets. • Perform feature engineering, model validation, and performance tuning. • Explore and deploy modern AI and ML approaches to enhance automation and analytics. Data Preparation & Quality • Prepare structured and unstructured data for modeling and advanced analysis. • Develop scripts and tools for data cleansing, validation, and enrichment. • Collaborate with Data Engineering to maintain efficient data pipelines. • Identify data quality issues and propose remediation. Analytics, Insights & Reporting • Conduct deep-dive analyses to identify trends and improvement opportunities. • Communicate complex findings in clear, concise ways to technical and non-technical stakeholders. • Support the development of dashboards, metrics, and analytical solutions. Cross-Team Collaboration • Work with architects, engineers, and analysts to define analytical requirements. • Contribute to conceptual data model design and workflow optimization. • Promote best practices in machine learning, analytics, and data governance.