Netscribes-Data Scientist

About Netscribes

Netscribes is a global leader in data, insights, and digital solutions, helping the world’s largest organizations accelerate growth and innovation. As a growth catalyst, we empower sales, marketing, product development, and strategy through a unique blend of domain expertise and technological capabilities. Our end-to-end solutions span data engineering, advanced analytics, AI, and intelligent automation—built to scale and adapt to dynamic business environments. We partner with clients across the implementation journey, aligning with their ecosystem to deliver actionable intelligence, operational efficiency, and competitive advantage. For more information

LoB Overview

Netscribes delivers integrated solutions across content, process, and technology to help global businesses scale efficiently and stay competitive in fast-moving markets.Our services are structured across three key areas:

Content Solutions

We specialize in building, managing, and optimizing large-scale content ecosystems for global brands. Our expertise spans product data enrichment, taxonomy development, catalog and digital shelf management, content operations, and digital asset optimization. These solutions help improve product discoverability, streamline content workflows, and enhance customer experience across digital platforms.

Process Solutions

Our research and insights-driven services support core business processes across marketing, product, customer experience, and operations. This includes market and competitive research, campaign analysis, customer intelligence, and content performance

tracking. Through Information Management Services (IMS) and managed service models, we embed scalable, high-quality support directly into client workflows, ensuring agility, consistency, and speed.

Technology Solutions

Complementing our content and process offerings, we bring advanced technology capabilities through data engineering, data analytics, and AI. From building unified data platforms and real-time dashboards to deploying intelligent automation and machine learning models, we help organizations modernize operations and unlock data-driven decisions at scale.

Profile Description

LOB: Operations | Technology Solutions

Role: Data Scientist

Designation: Senior Associate

Employment

Type: Permanent

Work Mode: Work From Office

Working Days: 5 days (Sat-Sun week off)

Shift: Fixed Shift (9 hours)

Shift Timings: General Shift

Location: Onsite.Pune

Key Responsibilities:

Role Overview

We are looking for a Data Scientist with exposure to manufacturing environments such as production, quality, supply chain, or IoT/sensor data. You will build models and analyses that turn operational and enterprise data into actionable insight — improving yield, reducing downtime, and supporting forecasting and decision-making across the shop floor and beyond.

Key Responsibilities

Modelling: Develop, validate, and deploy machine learning and statistical models for use cases such as predictive maintenance,

quality prediction, and demand forecasting.

Analysis: Perform exploratory analysis on production, quality, and supply chain data to surface patterns and root causes.

Feature engineering: Engineer features from manufacturing and time-series/sensor data to improve model performance.

Experimentation: Design and evaluate experiments, quantifying business impact and model reliability.

Deployment: Partner with data engineers to operationalise models into production pipelines and monitoring.

Collaboration: Work with manufacturing, quality, and supply

chain stakeholders to frame problems and translate results into

decisions.

Communication: Present findings and recommendations clearly to both technical and non-technical audiences.

Documentation: Maintain reproducible code, experiment tracking, and clear documentation of methods and assumptions.

Required Qualifications

Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.

3–6 years of experience building and deploying machine learning or statistical models.

Strong Python skills, including data science libraries (pandas, scikit-learn, NumPy).

Solid grounding in statistics, machine learning, and experimental design.

Strong SQL and experience working with large datasets.

Exposure to manufacturing, industrial, or IoT data (production, quality, supply chain, or time-series/sensor data).

Ability to communicate technical results to business stakeholders.

Preferred Qualifications

Experience with deep learning or time-series forecasting frameworks (PyTorch, TensorFlow, Prophet).

Familiarity with MLOps practices and tools (MLflow, model monitoring, CI/CD).

Knowledge of manufacturing metrics and processes (OEE, yield,

predictive maintenance, supply chain).

Experience with a cloud platform (AWS, Azure, or GCP) and big-

data tooling (Spark/Databricks).

Education: Graduates only (please ignore pursuing/drop out/12th or 10th pass)