Senior Data Scientist

Company Overview

Osol Tech Pvt. Ltd. is a fast-growing software development and professional services company, pioneering AI/ML-driven innovation across industries. We empower organizations in manufacturing, healthcare, retail, and e-commerce to make smarter, data-driven decisions through advanced analytics, predictive modeling, and AI solutions. Our culture fosters continuous learning, collaboration, and innovation at scale.

Job Summary

We are seeking a Senior Data Scientist to lead the design and implementation of advanced analytics and data science solutions. This role requires a strong foundation in statistics, machine learning, data engineering, and domain-driven problem solving.

The ideal candidate will have experience building end-to-end data science solutions — from exploratory data analysis and feature engineering to production-ready models and business insights. You will collaborate closely with engineers, analysts, and business stakeholders to drive measurable outcomes.

Key Responsibilities

• Design, build, and evaluate predictive and prescriptive models (regression, classification, forecasting, clustering, recommendation systems).
• Apply advanced ML methods (gradient boosting, ensemble models, transformers for tabular/text, probabilistic models).
• Conduct A/B tests and causal inference to measure business impact.
• Perform exploratory data analysis (EDA) using statistical and visualization tools.
• Translate data findings into actionable insights with clear storytelling for non-technical audiences.
• Build dashboards and reports to support decision-making.
• Work with SQL, Spark, Dask, or BigQuery to process and transform large datasets.
• Collaborate with data engineers to ensure high-quality, reliable data pipelines.
• Apply feature engineering, data augmentation, and missing data handling strategies.
• Contribute to model deployment using MLflow, SageMaker, Vertex AI, or Azure ML.
• Support model monitoring and retraining strategies.
• Use Python (Pandas, NumPy, Scikit-learn, Statsmodels, PyTorch/TensorFlow), R, SQL, and Jupyter for analysis and modeling.
• Use visualization & BI tools (Matplotlib, Seaborn, Plotly, Power BI, Tableau, Looker).
• Track experiments with MLflow, DVC, or Weights & Biases.
• Partner with product managers and business teams to frame problems and define success metrics.
• Mentor junior data scientists and analysts.
• Champion data-driven decision-making across the organization.

Required Qualifications & Skills

• Strong programming skills in Python and SQL; familiarity with R or Julia is a plus.
• Solid foundation in statistics, probability, linear algebra, and hypothesis testing.
• Experience with machine learning techniques (supervised/unsupervised learning, ensembles, time series).
• Proficiency with data visualization and ability to communicate insights effectively.
• Hands-on experience with big data tools (Spark, Dask, BigQuery).
• Cloud experience with AWS, GCP, or Azure for data science workflows.
• Familiarity with version control (Git), experiment tracking, and reproducible workflows.
• Excellent communication, collaboration, and problem-solving skills.
• Proven ability to mentor junior engineers and lead initiatives.

Preferred Qualifications

• Domain expertise in manufacturing, healthcare, retail, or e-commerce applications.
• Experience with NLP or computer vision applied to data-rich use cases.
• Hands-on experience with causal inference, Bayesian methods, or reinforcement learning for experimentation.
• Prior open-source contributions, publications, or patents.
• Experience with BI/analytics strategy and executive-level presentations.

Education & Experience

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.

• PhD or strong research experience is a plus, but not required.

• 5–7+ years of professional experience in data science or advanced analytics, with evidence of driving business impact.

What We Offer

• High-impact data science projects that solve real-world problems.
• Continuous learning opportunities with cloud credits, courses, and conference sponsorships.
• Competitive salary, benefits, and performance-based incentives.
• Flexible hybrid/remote working environment.
• A culture of collaboration, innovation, and knowledge sharing.