Data Scientist (Expert Level

Overview

Are you passionate about leveraging data to drive strategic decisions and unlock hidden opportunities? Our organization is seeking an Expert-Level Data Scientist with a knack for uncovering trends, developing cutting-edge machine learning models, and communicating insights through compelling visualizations. We believe India is home to some of the sharpest data minds, and we’re committed to bringing your expertise onboard to tackle high-impact, global challenges.

Mission & Vision

We’re on a mission to harness the power of data to inform business strategy, optimize processes, and deliver measurable improvements across diverse industries. By combining innovative analytical methods with scalable technologies, we aim to build AI-driven solutions that revolutionize how businesses operate. If you thrive on transforming massive datasets into actionable insights, you’ll find the perfect environment here.

Why We’re Targeting Expert-Level Talent

Data Science today demands more than just coding skills. We need professionals who can:

• Pinpoint the right questions before diving into the data, ensuring every analysis is value-driven.
• Architect predictive models that drive impactful decisions, balancing accuracy, interpretability, and performance.
• Implement robust, production-ready pipelines that withstand large-scale data and adapt to ever-evolving use cases.
• Mentor and guide team members, lifting the overall analytics and data science capabilities of the organization.

Role Overview

As an Expert Data Scientist, you will own the entire data lifecycle—from data gathering and cleaning, to statistical modeling, deployment, and continuous improvement. You’ll collaborate with engineers, product managers, and business stakeholders to ensure that data science solutions align closely with organizational goals. You’ll also champion best practices in data governance, security, and compliance.

Key Responsibilities

• Data Analysis & Exploration
• Dive deep into complex datasets to uncover trends, correlations, and anomalies.
• Perform exploratory data analysis (EDA), leveraging statistical techniques and visualization tools.
• Machine Learning Model Development
• Build predictive models (regression, classification, time-series forecasting) using Python, R, and ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Optimize hyperparameters, validate performance, and iterate to achieve production-grade accuracy.
• Data Pipeline Optimization
• Collaborate with data engineering teams to design efficient pipelines for data extraction, transformation, and loading (ETL).
• Ensure workflows are reproducible, scalable, and resilient to handle large, streaming data sources.
• Interactive Data Visualizations
• Use Tableau, Power BI, or custom dashboards to present findings in an accessible, action-oriented manner.
• Communicate complex metrics in clear, visually compelling formats to support data-driven decisions.
• Cross-Functional Collaboration
• Partner with engineering, product, and business teams to embed AI solutions into existing products or workflows.
• Provide domain-specific insights, guiding teams on what data to collect and how to interpret results.
• Data Quality & Governance
• Uphold industry standards for data security, privacy, and compliance (GDPR, HIPAA, etc.).
• Conduct regular data audits, monitor data drift, and maintain documentation to ensure high-quality, reliable datasets.
• Continuous Improvement & Innovation
• Experiment with deep learning (NLP, computer vision) or advanced techniques like reinforcement learning when relevant.
• Stay abreast of MLOps tools (MLflow, Kubeflow, DataRobot) to streamline model deployment and monitoring.

Requirements

• Education: Bachelor’s/Master’s/PhD in Computer Science, Statistics, Mathematics, or a related field.
• Technical Mastery: Proficiency in Python, R, SQL for data manipulation and modeling. Familiarity with frameworks like TensorFlow, PyTorch, Scikit-learn.
• Statistical Rigor: Deep understanding of statistical analysis, hypothesis testing, and A/B testing methodologies.
• Cloud & Big Data: Hands-on experience with AWS, GCP, or Azure, as well as big data tools like Spark or Hadoop.
• Soft Skills: Outstanding communication, presentation, and problem-solving abilities; capable of conveying complex insights to both technical and non-technical stakeholders.

Preferred Qualifications

• Advanced Specializations: NLP, deep learning (CNNs, RNNs), or reinforcement learning.
• MLOps Expertise: Familiarity with MLflow, Kubeflow, or DataRobot to manage end-to-end model lifecycles.

Job Type: Full-time

Pay: ₹15,000.00 - ₹20,000.00 per month

Benefits:

• Flexible schedule

Schedule:

• Monday to Friday
• Weekend availability

Work Location: Remote