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Weekday AI (YC W21)
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Data Scientist

Data Scientist

Weekday AI (YC W21)

10 years

80 - 90 Lacs

bengaluru karnataka india

Posted:2 days ago| Platform:

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Skills Required

data learning ml drive vision leadership analytics technology development design optimization strategy architecture preprocessing engineering model evaluation deployment algorithms scalability interpretability ai collaboration governance transparency compliance regulations monitoring tracking drift analysis experimentation statistics mathematics python scala tensorflow pytorch xgboost sql nosql aws sagemaker azure gcp versioning containerization docker kubernetes probability communication management

Work Mode

On-site

Job Type

Full Time

Job Description

This role is for one of the Weekday's clients

Salary range: Rs 8000000 - Rs 9000000 (ie INR 80-90 LPA)

Min Experience: 10 yearsLocation: BengaluruJobType: full-timeWe are seeking a highly experienced

Data Scientist

with a strong foundation in

Machine Learning (ML)

to lead complex data-driven initiatives and contribute to strategic decision-making. The ideal candidate will have deep technical expertise, a proven record of delivering scalable ML solutions, and the ability to collaborate cross-functionally to drive innovation through data. This role requires both strategic vision and hands-on technical leadership, making it ideal for someone who thrives at the intersection of analytics, technology, and business impact.

Requirements

Key Responsibilities

Machine Learning Development: Design, build, and deploy advanced ML models for prediction, classification, recommendation, and optimization across business domains.
Data Strategy & Architecture: Lead the end-to-end data science lifecycle — from data collection, preprocessing, and feature engineering to model evaluation and deployment in production environments.
Algorithmic Innovation: Develop and refine algorithms to enhance performance, scalability, and interpretability. Stay abreast of the latest trends and advancements in ML, deep learning, and AI.
Cross-functional Collaboration: Partner closely with data engineering, product, and business teams to translate complex problems into actionable ML-driven solutions.
Model Governance: Ensure model transparency, reproducibility, and compliance with data privacy regulations and ethical AI standards.
Mentorship & Leadership: Guide junior data scientists and analysts, fostering a culture of technical excellence and continuous learning within the team.
Performance Monitoring: Establish frameworks for model performance tracking, drift detection, and continuous improvement post-deployment.
Business Insight Generation: Leverage statistical analysis, predictive modeling, and machine learning techniques to uncover trends and patterns that drive business outcomes.
Tool & Framework Optimization: Champion the adoption of modern ML frameworks, libraries, and cloud-based platforms to streamline experimentation and deployment workflows.

Qualifications & Skills

Education: Master's or Ph.D. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.

Experience: 10-15 years of experience in data science or applied machine learning, with a track record of developing and deploying production-grade models.

Technical Expertise:

Proficiency in Python, R, or Scala for data manipulation and model development.
Strong understanding of machine learning algorithms, deep learning architectures (CNNs, RNNs, Transformers), and NLP frameworks.
Hands-on experience with TensorFlow, PyTorch, Scikit-learn, and XGBoost.
Solid grasp of data pipelines, SQL/NoSQL databases, and cloud ML platforms (AWS Sagemaker, Azure ML, or GCP AI Platform).
Familiarity with MLOps practices, including model versioning, CI/CD for ML, and containerization using Docker or Kubernetes.
Analytical Mindset: Strong command of statistics, probability, and optimization techniques.
Soft Skills: Excellent problem-solving, communication, and stakeholder management abilities, with the capacity to explain complex technical concepts to non-technical audiences

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Data Scientist