Job Specifications
We are seeking a Senior Data Scientist / Machine Learning Engineer to design, develop, and operationalize advanced analytics, machine learning, and generative AI solutions in an enterprise environment.
This role combines hands-on coding, advanced analytics, ML engineering, and MLOps, with a strong focus on Azure Databricks, PySpark, Python, SQL, Power BI, and GenAI/LLM solutions.
The ideal candidate is equally comfortable building models, deploying them into production, and explaining insights to business stakeholders.
Key Responsibilities
Advanced Analytics & Machine Learning
Design, develop, and optimize machine learning models (forecasting, classification, clustering)
Apply data mining techniques to uncover trends and patterns
Perform feature engineering, model validation, and performance tuning
Explore and deploy Generative AI and LLM-based solutions
Apply NLP techniques for text analytics and unstructured data use cases
Data Preparation & Quality
Prepare structured and unstructured datasets for advanced analytics
Develop Python and PySpark scripts for data cleansing, validation, and enrichment
Collaborate with Data Engineering teams to maintain efficient pipelines
Identify data quality issues and propose remediation strategies
MLOps & Productionization
Implement Machine Learning Operations (MLOps) practices
Deploy, monitor, and maintain models in production environments
Manage model lifecycle, versioning, and retraining
Ensure scalability, reliability, and performance of ML solutions
Analytics, Insights & Reporting
Conduct deep-dive analyses to support diagnostic and predictive insights
Develop and support Power BI dashboards, DAX queries, and reporting best practices
Perform root-cause analysis of data and dashboard issues
Translate complex analytics into actionable business insights
Cross-Functional Collaboration
Work with architects, engineers, analysts, and business stakeholders
Contribute to data model design and analytics workflow optimization
Promote best practices in analytics, machine learning, and data governance
Required Skills & Experience
Education
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field
Core Technical Skills
7+ years of experience in data science and machine learning engineering
Strong Python expertise (data science & ML workloads)
Advanced SQL skills with relational databases
PySpark programming (required)
Strong understanding of statistical modeling and machine learning algorithms
Experience with Azure Databricks (certification preferred)
Experience with Generative AI and Large Language Models (LLMs)
Strong background in MLOps
Experience with Natural Language Processing (NLP)
A/B Testing and experimental analysis experience
Strong coding background with production-quality standards
Data & Visualization
3+ years experience with Power BI, DAX queries, and visualization best practices
Ability to analyze and resolve dashboard/data issues
Nice to Have
Google Cloud experience (BigQuery preferred)
Oracle database experience
Azure Databricks Data Engineer Professional Certification
Data Analyst background with ML exposure
Knowledge of statistical methods and experimental design
About the Company
At Call Quest Solutions, we believe great companies are built by great people. Since our founding, we’ve become one of the most trusted staffing and recruitment agencies in the U.S., serving businesses of all sizes—from high-growth startups to established Fortune 500 enterprises. Our mission is simple: connect exceptional talent with meaningful opportunities. We specialize in Direct Hire, Contract & Temporary Staffing, and Executive Search, delivering workforce solutions tailored to each client’s unique needs. With a nationa...
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