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Data Specialist
As a Data Specialist with Azure and Apache platforms experience, you will be responsible for analyzing large datasets, developing predictive models, and deploying scalable data solutions. Your role will involve utilizing both Azure and Apache technologies to drive data-driven insights and optimize business processes.
Key Responsibilities:
Data Analysis and Modeling:
Analyze large and complex data sets to extract actionable insights and identify patterns.
Develop, validate, and deploy machine learning models and predictive analytics to address business challenges.
Perform data preprocessing, feature engineering, and data transformation to ensure high-quality data for analysis.
Azure and Apache Platforms:
Design, develop, and deploy data science solutions using Azure Machine Learning, Azure Databricks, Azure Synapse Analytics, and other Azure services.
Utilize Apache Spark, Hadoop, Kafka, and other Apache tools for big data processing and real-time analytics.
Implement data integration and ETL processes using Azure Data Factory and Apache NiFi.
Collaboration and Communication:
Work closely with data engineers, software developers, and business stakeholders to understand business requirements and translate them into data science projects.
Communicate findings and insights effectively through visualizations, presentations, and reports.
Collaborate with the IT and DevOps teams to ensure seamless deployment and integration of data science models into production environments.
Research and Innovation:
Stay current with the latest advancements in data science, machine learning, and cloud technologies.
Continuously explore new tools, techniques, and best practices to improve the efficiency and effectiveness of data science processes.
Contribute to the development of a data-driven culture within the organization.
Qualifications:
Education:
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
Relevant certifications (e.g., Microsoft Certified: Azure Data Scientist Associate, Apache Spark Developer) are a plus.
Experience:
3+ years of experience in data science, machine learning, or a related field.
Proven experience with Azure data services (Azure Machine Learning, Azure Databricks, Azure Synapse Analytics, Azure Data Factory).
Strong experience with Apache platforms (Apache Spark, Hadoop, Kafka, NiFi).
Proficiency in programming languages such as Python, R, and SQL.
Experience with data visualization tools such as Power BI, Tableau, or similar.
Technical Skills:
Proficiency in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
Strong understanding of statistical analysis, data mining, and predictive modeling techniques.
Experience with big data technologies and distributed computing (e.g., Apache Spark).
Soft Skills:
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication and presentation skills.
Ability to translate complex data findings into actionable business insights.
Benefits:
Competitive salary and performance-based bonuses.
Comprehensive health, dental, and vision insurance.
Retirement savings plan with company match.
Professional development opportunities and continuing education support.
Flexible work hours and remote work options.
AI Engineer
As an AI Engineer, you will design, develop, and deploy AI models and solutions using open-source frameworks and the Azure Open AI platform. You will collaborate with cross-functional teams to create innovative AI applications that enhance business processes and deliver value to our customers.
Key Responsibilities:
Model Development and Deployment:
Design, develop, and deploy AI models using open-source frameworks such as TensorFlow, PyTorch, scikit-learn, and Llama LLM.
Implement RAG (Retrieval-Augmented Generation) techniques and Agentic development to create intelligent and responsive AI systems.
Utilize the Azure Open AI suite of platforms for model training, deployment, and management.
Data Processing and Feature Engineering:
Preprocess and transform large datasets to create features suitable for AI model training.
Perform data augmentation, normalization, and other data preparation techniques to enhance model performance.
Integration and Scalability:
Integrate AI models into existing systems and workflows, ensuring seamless functionality and scalability.
Use Azure services such as Azure Machine Learning, Azure Databricks, and Azure Cognitive Services to scale and manage AI solutions.
Collaboration and Communication:
Work closely with data scientists, software engineers, and business stakeholders to understand requirements and translate them into AI solutions.
Communicate complex AI concepts and results to non-technical stakeholders through presentations, reports, and visualizations.
Research and Innovation:
Stay up-to-date with the latest advancements in AI, machine learning, and open-source frameworks.
Experiment with new algorithms, techniques, and tools to continuously improve AI capabilities and performance.
Qualifications:
Education:
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Relevant certifications (e.g., TensorFlow Developer, Microsoft Certified: Azure AI Engineer Associate) are a plus.
Experience:
3+ years of experience in AI, machine learning, or a related field.
Proven experience with open-source AI frameworks (TensorFlow, PyTorch, scikit-learn, Llama LLM).
Strong experience with the Azure Open AI suite of platforms, including Azure Machine Learning, Azure Databricks, and Azure Cognitive Services.
Technical Skills:
Proficiency in programming languages such as Python, R, and SQL.
Deep understanding of machine learning algorithms, neural networks, and natural language processing techniques.
Experience with RAG (Retrieval-Augmented Generation) and Agentic development.
Soft Skills:
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication and presentation skills.
Ability to translate complex technical concepts into actionable business insights.
Benefits:
Competitive salary and performance-based bonuses.
Comprehensive health, dental, and vision insurance.
Retirement savings plan with company match.
Professional development opportunities and continuing education support.
Flexible work hours and remote work options.
