Data Scientist

Spectrum Talent Management; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Spectrum Talent Management in India is seeking an experienced Data Scientist to deliver advanced analytics projects that drive business results, including data cleaning, exploratory analysis, model building, and polished deliverables.

You will analyze large-scale data across retail, marketing, and operations, collaborate with data engineers, and present insights to stakeholders using modern BI and visualization tools.

Qualifications

• Bachelor’s degree in a quantitative field (Statistics, Analytics, Data Science, Math, Economics) is required.
• Master’s degree preferred (MBA/MS CS, etc.)

Responsibilities

• Deliver advanced analytics projects from data cleaning to polished deliverables.
• Analyse large-scale structured and unstructured data to develop deep-dive analyses and ML models in diverse business areas.
• Collaborate with Data Eng, BI, and stakeholders to implement scalable analytics and reporting solutions.
• Apply ML techniques and experiment design to derive actionable business insights.

Skills

Delivery Excellence

Business disposition

Social intelligence

Innovation and agility

Education

Bachelor’s degree required

Master’s degree preferred

Tools

Python

R

KNIME

MLflow

Docker

PyTorch

TensorFlow

AWS

Azure

GCP

Hadoop

Spark

MySQL

Microsoft SQL Server

MongoDB

DynamoDB

Power BI

Tableau

Alteryx

Job description

Role & responsibilities

The incumbent will be responsible for delivering advanced analytics projects that drive business results including interpreting business, selecting the appropriate methodology, data cleaning, exploratory data analysis, model building, and creation of polished deliverables.

Analytics & Strategy

• Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business
• Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data
• Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions
• Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional data

Operational Excellence

• Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project
• Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems
• Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analyses.

Stakeholder Engagement

• Working collaboratively across multiple sets of stakeholders Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables
• Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats

Job Requirements

Education

• Bachelor’s degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)
• Master’s degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)

Relevant Experience

• 3 - 4 years for Data Scientist
• Relevant working experience in a data science/advanced analytics role

Behavioural Skills

• Delivery Excellence
• Business disposition
• Social intelligence
• Innovation and agility

Knowledge

• Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)
• Statistical modelling using Analytical tools (R, Python, KNIME, etc.)
• Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)
• Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.
• Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.)
• Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)
• Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)
• Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools
• Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)
• Microsoft Office applications (MS Excel, etc.)