Data Science Data Science Senior Data Scientist

2 weeks ago

Bangalore, India Tundra Technical Solutions Full time

Tundra Technical Solutions is among North America's leading providers of Information Technology, Engineering staffing and consulting services. Our success and our clients' success are built on a foundation of service excellence. Rather than continually trying to sell to new clients and companies and simply filling databases with candidates, we focus on developing stronger relationships and deeper knowledge of our existing clients' challenges and opportunities. Tundra is a global provider of innovative staffing solutions and services. Tundra operates with a straightforward Vision – “To be the number one representative of choice for top talent across the globe”. Tundra’s proven ability to attract, engage and maintain relationships with the most talented resources worldwide is the fuel that empowers this success. Tundra values the talent we work with, and we are invested in creating meaningful relationships, we respect your time and experience and accredit OUR success to YOURS. We’re Hiring: Senior Data Scientist at Tundra Technical Solutions Bangalore (Hybrid) Shift : EST Experience : 7- 12 years Proficiency in Python with advanced use of NumPy, Pandas, and Scikit-learn • Expertise in SQL, including complex queries and performance optimization • Strong foundation in machine learning techniques (regression, classification, clustering, ensemble methods) • Experience in data visualization (Seaborn, Plotly, Tableau, or Power BI) • Hands-on experience with cloud-based ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) • Exposure to large-scale data processing (Spark, Hadoop) Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI • MLOps practices (MLFlow, Kubeflow, CI/CD pipelines for ML workflows) • Data pipeline orchestration (Airflow, Prefect) • Preparing and preprocessing structured and unstructured data for analysis • Designing, training, and validating machine learning models • Building dashboards and data-driven visual insights for stakeholders • Monitoring, optimizing, and retraining models for performance improvements Website :

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