Data Scientist

Overview

Develop and deploy predictive models, analyze data, and collaborate with stakeholders.

Key Responsibilities

• model development
• model deployment
• data visualization
• experiment design
• data engineering
• data governance

Tasks

-Stay up to date with emerging trends, tools, and techniques in data science and AI. -Build scalable, production-ready models and monitor their performance over time. -Present insights, findings, and recommendations through visualizations and storytelling. -Design and run experiments to validate hypotheses and measure outcomes. -Develop and implement machine learning models, predictive algorithms, and statistical analyses. -Collaborate with cross-functional teams to translate business problems into analytical solutions. -Collect, preprocess, and analyze structured and unstructured data from multiple sources. -Ensure data integrity, quality, and compliance with company standards and policies.

Requirements

• sql
• python
• spark
• aws
• phd
• tableau

What You Bring

-Effective at cross-functional/cross-cultural teamwork -Discretion when dealing with confidential information -Proficiency in SQL and working with large datasets. -Strong communication skills to explain complex concepts to both technical and non-technical audiences. -Experience with data visualization tools (Tableau, Power BI, matplotlib, seaborn, etc.). -Strong programming skills in Python or R, with experience in libraries/frameworks (e.g., pandas, scikit-learn, TensorFlow, PyTorch). -Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field. -Experience with big data technologies (Hadoop, Spark, or Databricks). -Familiarity with cloud platforms (AWS, GCP, or Azure). -Background in natural language processing (NLP), computer vision, or deep learning. -Knowledge of MLOps practices and model deployment pipelines. -Proven experience as a Data Scientist or in a similar role with the project details -Responsive to operational needs and sense of urgency -Experience in a specific domain (finance, healthcare, e-commerce, etc.) is a plus. -Strong understanding of statistical modeling, machine learning algorithms, and data mining techniques. -Available to work on US time zone or mixed -Excellent problem-solving skills and business acumen.

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About Quest Global

-By blending deep technical know‑how with digital innovation, it evolved into a global engineering partner. -Projects range from next‑gen automotive safety systems and AI‑driven semiconductors to cutting‑edge aerospace and defense platforms. -Its financial growth is steady—built on recurring partnerships with Fortune‑top‑10 clients across key sectors. -A hallmark project: sustaining global EMS/ADMS energy‑management software for a major utilities provider. -Another standout: accelerating MRI development and support globally for a leading MedTech firm. -Its edge lies in full‑lifecycle delivery—concept, design, embedded software, manufacturing support, digital sustenance. -Known for foresight, the firm not only solves challenges but anticipates and prevents them.

Sector Specialisms