Data Scientist

Qtsolv; Pune District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Qtsolv is seeking an experienced Data Scientist to drive data-driven decisions across supply chain planning, forecasting, optimization, and related areas. You will handle large enterprise datasets, develop predictive models, and collaborate with SCM SMEs, data engineers, and technology teams to translate business needs into analytical solutions.

The ideal candidate has 5-8 years in Data Science/ML, strong Python and SQL skills, and hands-on experience with ERP data and supply chain ontologies.

Qualifications

• 5-8 years of experience in Data Science/ML/Advanced Analytics.
• Strong proficiency in Python with Pandas, NumPy, Scikit-learn.
• Solid understanding of ML, Statistical Modelling, Predictive Analytics, Forecasting, Optimization.
• Experience in data preprocessing, feature engineering, model evaluation, tuning.
• Familiarity with Supply Chain Ontology.
• Exposure to the Manufacturing domain.
• Understanding ERP data.
• Ability to map relationships between supply chain entities (products, locations, suppliers, customers, inventory, demand, supply).
• Experience with structured and unstructured enterprise datasets.
• Strong SQL and relational databases.
• Knowledge of data quality, transformation, modelling concepts.
• Experience with cloud-based data and analytics environments.
• Strong problem-solving, analytical, and communication skills.

Responsibilities

• Develop, implement, and deploy ML and statistical models for supply chain problems.
• Perform EDA, feature engineering, data preparation, model development, validation, and tuning.
• Work with large enterprise datasets and extract meaningful insights.
• Apply ML, forecasting, optimization to supply chain use cases.
• Collaborate with stakeholders, SCM SMEs, data engineers, and tech teams.
• Understand Supply Chain Ontology and ERP data structures.
• Translate business requirements into analytical solutions.
• Operationalize models and integrate analytics into enterprise apps.

Skills

Data Science

Python

SQL

Analytics

Communication

Problem solving

Model evaluation

Forecasting

Education

Bachelor's or Master's in CS/DS/Statistics/Engineering

Advanced degree in Data Science/OR/Supply Chain

Tools

Pandas/NumPy/Scikit-learn

ERP data familiarity

Snowflake/Databricks/Spark

Docker/Kubernetes/CI/CD

Blue Yonder / o9 IBP tools

AWS/Azure/GCP

Job description

We are looking for an experienced Data Scientist with strong expertise in machine learning, statistical modelling, data analysis, and predictive analytics, along with a solid understanding of Supply Chain and Manufacturing domain concepts.

The ideal candidate should have hands‑on experience working with complex enterprise data and demonstrate familiarity with Supply Chain Ontology, Manufacturing processes, and ERP data structures. The candidate will be responsible for developing data-driven solutions that address business problems across supply chain planning, forecasting, optimization, and related areas.

Key Responsibilities

• Develop, implement, and deploy machine learning and statistical models to solve complex business and supply chain problems.
• Perform exploratory data analysis, feature engineering, data preparation, model development, validation, and performance optimization.
• Work with large and complex datasets from enterprise systems and identify meaningful business insights.
• Apply machine learning, predictive analytics, optimization, forecasting, and statistical techniques to supply chain use cases.
• Collaborate with business stakeholders, supply chain SMEs, data engineers, and technology teams to translate business requirements into analytical solutions.
• Understand and work with Supply Chain Ontology, including relationships between products, locations, suppliers, customers, inventory, demand, supply, and other supply chain entities.
• Leverage understanding of Manufacturing domain processes to develop relevant data science solutions.
• Work with and interpret ERP data, including understanding ERP data structures, master data, transactional data, and relationships between key business entities.
• Identify data quality issues, perform data profiling, and recommend improvements to support reliable analytics and modelling.
• Build scalable data science solutions and contribute to productionizing machine learning models.
• Communicate analytical findings, model outcomes, and business recommendations effectively to technical and non‑technical stakeholders.
• Collaborate with engineering teams to operationalize models and integrate data science solutions into enterprise applications and platforms.

Key Skills - Mandatory

• 5-8 years of experience in Data Science / Machine Learning / Advanced Analytics.
• Strong proficiency in Python, with experience using libraries such as Pandas, NumPy, Scikit-learn, and relevant ML frameworks.
• Strong understanding of Machine Learning, Statistical Modelling, Predictive Analytics, Forecasting, and Optimization.
• Experience in data preprocessing, feature engineering, model evaluation, and model performance tuning.
• Familiarity with Supply Chain Ontology
• Exposure to the Manufacturing domain
• Understanding and familiarity with ERP data
• Ability to understand relationships between supply chain entities such as products, materials, locations, suppliers, customers, inventory, demand, and supply.
• Experience working with structured and unstructured enterprise datasets.
• Strong SQL and experience working with relational databases.
• Good understanding of data quality, data transformation, and data modelling concepts.
• Experience working with cloud‑based data and analytics environments.
• Strong problem‑solving, analytical, and communication skills.

Preferred Skills

• Data Scientists who have worked extensively with ERP data are preferred.
• Experience working with Blue Yonder, o9 Solutions, or similar Integrated Business Planning (IBP) / Supply Chain Planning tools is highly preferred.
• Experience in supply chain planning, demand forecasting, inventory optimization, supply planning, or manufacturing analytics.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with MLOps, model deployment, ML pipelines, Docker, Kubernetes, or CI/CD.
• Experience with data platforms such as Snowflake, Databricks, Spark, or similar technologies.
• Familiarity with supply chain planning and optimization frameworks is an advantage.

Education

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative discipline.
• Advanced degree in Data Science, Machine Learning, Operations Research, Supply Chain, or a related field is preferred.

Candidate Profile

The ideal candidate is a Data Scientist with strong technical expertise and relevant functional/domain knowledge, particularly across Supply Chain and Manufacturing. Candidates should be comfortable working with Supply Chain Ontology and ERP data and translating business problems into data-driven solutions.

Experience with ERP systems, Blue Yonder, o9, or similar IBP platforms will be an added advantage.