Job DescriptionWe are seeking experienced
Data Analytics / Data Science professionals with 4-8 years of hands-on experience in data analysis, statistical modeling, business intelligence, and/or machine learning. The ideal candidate will have strong expertise in
SQL, Python, data visualization, statistical analysis, data modeling, and modern cloud-based data platforms, with the ability to translate complex datasets into actionable business insights.
Experience with
modern AI/ML, Generative AI, LLMs, and AI-assisted analytics is highly desirable.
Experience: 4-8 Years
Employment Type: Full-Time W2 Only
Work Authorization: U.S. Citizen / Green Card / H4 EAD
Location: Open to opportunities across the United States
Relocation: Must be willing to relocate anywhere in the U.S. for a suitable opportunity
Key Responsibilities- Collect, clean, transform, and analyze structured and unstructured data.
- Perform Exploratory Data Analysis (EDA) and identify trends, patterns, anomalies, and business opportunities.
- Develop dashboards, reports, and data visualizations using Power BI, Tableau, or equivalent tools.
- Write complex and optimized SQL queries for data extraction and analysis.
- Develop statistical models and machine learning solutions for business problems.
- Build and evaluate predictive models using appropriate ML algorithms.
- Perform feature engineering, model validation, and performance evaluation.
- Work with large-scale datasets using modern data processing technologies.
- Collaborate with data engineers, software engineers, product teams, and business stakeholders.
- Communicate analytical findings and recommendations to technical and non-technical stakeholders.
- Support data quality, governance, validation, and documentation initiatives.
- Deploy and monitor analytical or machine learning models in production environments where applicable.
- Leverage AI/GenAI tools to improve data analysis, reporting, automation, and productivity.
Cloud & Modern Data TechnologiesExperience with one or more of the following:- AWS, Microsoft Azure, or Google Cloud Platform (GCP)
- Snowflake, Databricks, BigQuery, Redshift, or Azure Synapse
- Cloud-based data warehouses and data lakes
- Apache Spark / PySpark
- ETL/ELT tools and modern data pipeline technologies
- Airflow, dbt, or equivalent data orchestration/transformation tools
- Data lakehouse architecture and distributed data processing
AI / Machine Learning / GenAIExperience with the following is highly desirable:
- Machine Learning using Scikit-learn, XGBoost, TensorFlow, or PyTorch
- Generative AI and LLM-based applications
- Experience working with OpenAI, Azure OpenAI, Amazon Bedrock, Google Vertex AI, or equivalent AI platforms
- RAG (Retrieval-Augmented Generation) concepts
- Embeddings and vector databases
- AI-powered analytics and intelligent automation
- LLM prompt engineering and evaluation
- Familiarity with LangChain, LlamaIndex, or similar frameworks
- Experience using AI coding/analytics assistants such as GitHub Copilot or equivalent tools
Data Engineering & Analytics Exposure- Experience working with large and complex datasets.
- Understanding of data pipelines, ETL/ELT, data ingestion, transformation, and orchestration.
- Exposure to Kafka or other event-streaming technologies is a plus.
- Understanding of data governance, lineage, security, and data quality practices.
- Experience with APIs and integrating data from multiple sources is desirable.
Preferred Qualifications- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Technology, or a related field.
- Experience building end-to-end analytics or data science solutions.
- Experience deploying ML models or analytical applications to cloud environments.
- Knowledge of MLOps and model lifecycle management.
- Experience with MLflow, Kubeflow, or equivalent platforms.
- Understanding of responsible AI, model monitoring, and AI governance.
- Experience presenting analytical insights to senior stakeholders.
Required Skills- 4-8 years of professional experience in Data Analytics, Data Science, Business Intelligence, or a related field.
- Strong proficiency in SQL, including complex queries, joins, CTEs, window functions, aggregations, and query optimization.
- Strong hands-on experience with Python for data analysis and/or data science.
- Experience with Pandas, NumPy, Matplotlib, Seaborn, or equivalent Python libraries.
- Strong understanding of statistics, probability, hypothesis testing, regression, and statistical analysis.
- Experience with data visualization and BI tools, such as Power BI, Tableau, Looker, or similar.
- Understanding of data modeling, ETL/ELT concepts, data quality, and data pipelines.
- Experience with machine learning concepts and frameworks, including Scikit-learn or equivalent.
- Experience working with relational databases such as PostgreSQL, MySQL, SQL Server, Oracle, or similar.
- Strong analytical, problem-solving, and communication skills.
- Experience working in Agile/Scrum environments.
Core Technology StackPython | SQL | Pandas | NumPy | Scikit-learn | PySpark | Power BI | Tableau | AWS | Azure | GCP | Snowflake | Databricks | BigQuery | Spark | Airflow | dbt | Machine Learning | Generative AI | LLMs | RAG | Vector Databases | GitCandidate Requirements
- 4-8 years of hands-on professional experience in Data Analytics/Data Science or related roles.
- Must be authorized to work in the U.S. as a U.S. Citizen, Green Card holder, or H4 EAD holder.
- W2 only.
- Must be willing to relocate anywhere in the United States for a suitable opportunity.
- Strong communication and stakeholder-management skills.
- Ability to work independently as well as collaboratively in cross-functional teams.
