layiq
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worthy; deserving; fitting; suitable.
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Job opportunity
Data Scientist
ShyftLabs
Noida, Uttar Pradesh
Source: ShyftLabs careers · View original posting
Employer job description
From ShyftLabs's posting. “We” and “our” refer to the employer.
Role Overview
We're looking for a Data Scientist to help turn our data into actionable insights and intelligent products. You'll work closely with engineering, product, and business teams to design experiments, build predictive models, and translate complex analysis into clear recommendations that drive decisions across the company.
- Key Responsibilities: Design, build, and validate machine learning models to solve business problems such as forecasting, segmentation, and recommendation
- Partner with product and engineering teams to translate business questions into well-scoped analytical problems
- Conduct exploratory data analysis to uncover trends, patterns, and actionable insights in large datasets
- Design and analyze A/B tests and other experiments to evaluate product and business decisions
- Build and maintain data pipelines in collaboration with data engineering for reliable, reproducible analysis
- Communicate findings clearly to both technical and non-technical stakeholders through reports, dashboards, and presentations
- Monitor deployed models for performance and drift, and iterate as needed
- Contribute to best practices around experimentation, model evaluation, and data quality
Requirements: Python
- Pandas
- NumPy
- Scikit-learn
- SQL
- Statistics & Experiment Design (A/B Testing)
- Machine Learning Model Development
- Preferred Skills: Data Visualization (Matplotlib/Seaborn/Tableau)
- TensorFlow
- PyTorch
- AWS SageMaker
- GCP Vertex AI
- Azure ML
- Model Deployment to Production
- MLOps (experiment tracking, model monitoring)
- Domain Expertise (finance/healthcare/e-commerce)
- Stakeholder Communication
- Qualifications: 3+ years of experience in a data science, applied ML, or quantitative analytics role
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL
- Solid grounding in statistics and experiment design, including A/B testing methodology
- Experience building and evaluating machine learning models for real-world problems
- Ability to communicate technical findings clearly to non-technical audiences