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We are looking for a highly motivated and skilled Data Scientist who also brings strong Data Engineering capabilities. This is a hybrid role with a primary focus on data science—developing advanced analytics and predictive solutions—while also requiring flexibility to support data engineering efforts and responsibilities when needed. You'll build data-driven applications that solve real-world business challenges and partner with both internal teams and customers to deliver high-impact outcomes.
Job Responsibility:
Partner with customers and internal stakeholders to identify business opportunities and deliver predictive, actionable solutions
Develop data-driven applications that solve real-world customer problems
Stay current with trends in machine learning and AI, and apply best-in-class tools, libraries, and technologies
Serve as a subject matter expert on generating insights from data and developing machine learning models
Design and build intuitive, interactive data visualizations to communicate findings
Lead pilot projects with customers, measure business value and impact
Transition successful pilots into production-ready commercial applications
Collaborate with platform architects to ensure designs align with security and architecture best practices
Review code and solutions before deployment to ensure quality and performance
Work with and oversee contractors to deliver high-quality outcomes
Design and develop high-performance data ingestion pipelines using Azure Databricks and Azure Data Factory
Work with event-based streaming technologies to process real-time data
Architect and implement scalable Data Lakehouse solutions
Support development and delivery of related components such as APIs and search functionality
Operate within Agile and DevOps frameworks to deliver iteratively from proof-of-concept to production
Ensure all engineering solutions meet security and enterprise architecture standards
Perform thorough code reviews to maintain high-quality standards
Requirements:
Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field
Strong grasp of algorithms, data structures, and software design principles
Strong forecasting experience- Time series forecasting, algorithms for forecasting, building predictive algorithms MLL algorithms
Experience with classification and regression modules
Hands-on experience with machine learning, NLP, and deploying models to production
Proficiency in Python and at least one JVM-based language (e.g., Java, Scala)
Proficiency in PySpark
Strong SQL and database design skills
5+ years of experience building and deploying end-to-end data science solutions
Analytical thinker with strong problem-solving abilities
Excellent written, verbal, and interpersonal communication skills
Thrives in a dynamic, fast-paced environment with shifting priorities
Proven ability to collaborate cross-functionally and influence stakeholders
Demonstrated commitment to fostering a diverse and inclusive workplace
Retail industry is a must have for the role
3+ years of relevant experience in data engineering roles
Strong knowledge of data management principles and best practices
Proven experience designing and building ETL pipelines
Expertise in Databricks, SQL, Azure Data Factory, Azure Data Lake, Azure Cosmos DB, and PySpark
Experience working with both structured and unstructured data
Background working in DevOps environments and familiarity with CI/CD practices
Ability to evaluate the scalability and performance of different tools and solutions
Nice to have:
Experience with classification and regression modules
Familiarity with event-based streaming technologies
Ability to evaluate the scalability and performance of different tools and solutions
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