Data Scientist

Company DescriptionFounded in 2023, Symhas is a Cloud consulting company specializing in AWS, GCP, Microsoft, and Oracle Cloud transformation solutions. With a strong foundation built on precision, expertise, and customer trust, Symhas empowers enterprises to modernize their cloud environments. The company's innovative approach ensures speed, scalability, and confidence in delivering tailored solutions to meet client needs. Symhas remains committed to driving meaningful cloud transformations for businesses across industries.Advanced Data Engineering & Architecture:Architects scalable data pipelines and ETL processes using Python(Pandas, NumPy) , SQL, and Cloud technologies (AWS/GCP/Azure). Capable of designing data models for both structured and unstructured data at scale.Machine Learning Leadership:Leads the end-to-end ML lifecycle, selecting appropriate algorithms for complex business problems. Proven track record of deploying high-impact models (Regression, Classification, Deep Learning, or NLP) that drive measurable business value. Should have working idea of GenAI and RAG architecture.Statistical Strategy & Experimentation:Designs and oversees complex A/B tests and causal inference studies using probability, hypothesis testing, statistical modeling and exploratory data analysis (EDA). Advises stakeholders on statistical validity and interprets data insights to guide strategic business decisions.MLOps & Production Excellence:Owns model reliability in production. Implements robust MLOps practices (CI/CD, model monitoring, drift detection) and collaborates with Engineering teams to ensure system scalability and latency requirements are met. Must have hands-on knowledge of production deployment and finetuningBig Data & Data Engineering Knowledge:Experience working with large-scale data processing frameworks such as Spark and Hadoop, and building efficient data pipelines.Mentorship & Collaboration :Mentors junior data scientists, conducts code reviews, and fosters a culture of best practices. Effectively communicates technical concepts to non-technical stakeholders and executive leadership.