Assistant Manager - Data Scientist

Praxy; Chennai District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Praxy is seeking an experienced Data Scientist to drive data‑driven decision making across the organization. You will translate complex data into actionable insights, build end‑to‑end machine learning solutions, and collaborate with product and engineering teams to define use cases and success metrics.

The role requires 8+ years in data science, strong Python and ML framework experience, and a solid background in statistics, data visualization, and cloud deployment.

Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science or a related field.
• 8+ years hands-on data science experience.
• Strong Python (Pandas, NumPy) and/or R.
• Solid statistics, probability, and experimental design knowledge.
• Experience with SQL and databases (relational/non-relational).
• Hands-on ML framework experience (Scikit-learn, XGBoost, TensorFlow/PyTorch).
• Experience with data visualization tools (Tableau/Power BI).
• Familiarity with cloud platforms (AWS/GCP/Azure) for deployment.

Responsibilities

• Design, build, and deploy ML models to solve business problems.
• Perform Exploratory Data Analysis to identify trends and anomalies.
• Collaborate with product, engineering and business teams to define use cases and metrics.
• Develop and maintain data pipelines with data engineering.
• Conduct A/B tests and experiments to validate hypotheses.

Skills

Python & ML libraries

SQL

Statistics & experimental design

Communication

Agile/Scrum

Data visualization

Cloud deployment

MLOps basics

NLP/Computer Vision

Education

Bachelor's/Master's in CS/Statistics/Data Science

Tools

Scikit-learn

TensorFlow / PyTorch

XGBoost

Spark / Hadoop

Kafka / Airflow

Docker / Kubernetes

MLflow

Tableau / Power BI

Job description

We are looking for an experienced DataScientist to join our team and drive data-driven decision-making across theorganization. The ideal candidate will have a strong foundation in statisticalanalysis, machine learning, and business problem-solving, with provenexperience translating data into actionable insights.

Key Responsibilities

• Design, build, and deploy machine learningmodels to solve business problems (classification, regression, clustering,recommendation systems, etc.)
• Perform exploratory data analysis (EDA) toidentify trends, patterns, and anomalies in large datasets
• Collaborate with product, engineering, andbusiness teams to define data science use cases and success metrics
• Develop and maintain data pipelines inpartnership with data engineering teams
• Conduct A/B testing and statisticalexperiments to validate hypotheses and measure impact
• Communicate findings and recommendations toboth technical and non-technical stakeholders through reports, dashboards, andpresentations
• Own end-to-end model lifecycle: from datacollection and feature engineering to model deployment and monitoring
• Stay current with the latest research andbest practices in data science and machine learning
• Mentor junior data scientists/analysts asneeded

Required Skills & Qualifications

• Bachelor's/Master's degree in ComputerScience, Statistics, Mathematics, Data Science, or a related field
• 8+ years of hands-on experience in datascience, applied machine learning, or a similar analytical role
• Strong proficiency in Python (Pandas, NumPy,Scikit-learn) and/or R
• Solid understanding of statistics,probability, and experimental design
• Experience with SQL and working withrelational/non-relational databases
• Hands-on experience with ML frameworks suchas Scikit-learn, XGBoost, TensorFlow, or PyTorch
• Experience with data visualization tools(Tableau, Power BI, or Matplotlib/Seaborn)
• Familiarity with cloud platforms (AWS, GCP,or Azure) for model deployment
• Strong problem-solving skills and ability towork with ambiguous business problems
• Excellent communication skills to presenttechnical findings to non-technical audiences
• Experience with MLOps tools (MLflow,Airflow, Docker, Kubernetes)
• Exposure to NLP, computer vision, ortime-series forecasting
• Experience working in Agile/Scrumenvironments
• Knowledge of big data tools (Spark, Hadoop)