Data Science

Hitachi Solutions

8 - 14 years

9 - 13 Lacs

Pune

Posted:1 day ago| Platform:

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Skills Required

Supply chain Data analysis data science Analytical Scheduling Manager Quality Control Monitoring Analytics SQL Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

We are seeking a talented and innovative Data Scientist to join our dynamic team in Pune, India. As a Data Scientist, you will play a crucial role in extracting valuable insights from complex datasets, developing advanced analytical models, and driving data-driven decision-making across our organization.

Experience: 8 - 14 years

Primary Skills: Data Science

Secondary Skills: Data Engineering/Data Analytics

Overview:

The role requires a skilled and versatile Data Scientist with strong experience in Natural Language Processing (NLP), Time Series Forecasting, and a working knowledge of Computer Vision (CV) techniques. The candidate will be working on cutting-edge AI applications with tangible business impact and collaborate with a diverse team of engineers, analysts, and domain experts and help us build holistic, multi-modal solutions.

Required Skills:
Minimum 5 years in a Data Science or ML role with direct experience in NLP and forecasting.
Proficient in Python and libraries like Pandas, NumPy, Scikit-learn, HuggingFace Transformers, and Prophet/ARIMA.
Strong understanding of model development lifecycle: from data ingestion to deployment.
Hands-on experience with SQL and data visualization (e.g., Seaborn, Matplotlib, Tableau).
Experience handling retail-specific data (ideally Apparel/Footwear) with seasonality, inventory, and sales nuances.
Familiarity with cloud platforms like AWS, GCP, or Azure for scalable model training and deployment.
Good to have:
Experience or interest in Computer Vision: object detection, OCR, or visual product search.
Familiarity with OpenCV, YOLO, CNNs, or OCR tools like Tesseract, EasyOCR.
Exposure to multi-modal ML systems (combining text, image, and tabular data).
Knowledge of API development (FastAPI, Flask) to expose ML models for product use.
Understanding of MLOps practices (e.g., CI/CD for ML, model monitoring).
Previous experience in fine-tuning LLMs or applying transfer learning in domain-specific NLP tasks.
Data Engineering:
- Experience in building and managing data pipelines using Azure Data Factory.
- Familiarity with Azure Synapse Analytics for data warehousing and analytics.
- Working knowledge of Azure Data Lake, Databricks on Azure, or Azure SQL for handling large-scale data.
- Good understanding of ETL/ELT processes, data transformation, and integration workflows in Azure ecosystem.
- Experience with scheduling, monitoring, and optimizing pipelines for ML data readiness.
Key Responsibilities:

Natural Language Processing:
Apply NLP techniques to extract insights from text data such as product descriptions, reviews, internal documents, and reports.
Fine-tune transformer-based models (e.g., BERT, RoBERTa, LLaMA) for classification, summarization, and named entity recognition.
Work with domain experts to create and maintain retail-specific taxonomies and knowledge structures.
Ensure model outcomes are explainable, ethical, and aligned with business needs.
Time Series Forecasting:
Analyze historical demand, inventory, and sales data to uncover trends and seasonality.
Utilize pre-trained models (e.g., ARIMA, Prophet, DeepAR) to generate accurate demand forecasts.
Fine-tune and adapt existing models using domain-specific data from the apparel/footwear industry.
Translate forecasts into actionable insights for supply chain, merchandising, and planning teams.
Good to have - Computer Vision:
Assist or contribute to CV projects involving product imagery, shelf monitoring, visual search, or quality control.
Apply basic CV techniques like image classification, object detection (e.g., using YOLO, OpenCV, or CNNs).
Support integration of image-based data into larger multi-modal ML systems.
Collaboration & Integration:
Work closely with cross-functional teams (e.g., Data Engineering, DevOps, Product, and Business Stakeholders).
Develop scalable, reusable ML components that can be deployed in production environments.
Participate in designing evaluation frameworks and A/B tests for forecasting and NLP model effectiveness.

Qualifications

Masters degree in Computer Science, Data Science, Statistics, or a related field
Proven experience in data science, machine learning, or a similar role
Strong proficiency in Python and SQL

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