Senior Data Scientist

Senior Data Scientist – Agentic AI, Machine Learning & Cloud MLOps

Company: Artefact
Client: UK-based Client
Industry: Data Science, AI & Management Consulting
Job Type: Full-time
Location: Pune, India (Offshore)
Experience: 3–6 Years
Openings: 4
Compensation: ₹24–27 LPA
Notice Period: 60–90 Days

Location Preference: Pune-based candidates are preferred. Candidates willing to relocate to Pune are also welcome.

About Artefact

Artefact is a global consulting firm specializing in accelerating the adoption of data and artificial intelligence. With approximately 1,800 employees across 25 countries and more than 1,000 client partnerships, Artefact combines data science, engineering, and consulting expertise to deliver measurable business impact.

Its clients include Nissan, L’Oréal, Carrefour, Orange, BNP Paribas, and Samsung.

Role Overview

Artefact is seeking a Senior Data Scientist to design, develop, and deploy advanced Agentic AI, machine learning, and data science solutions for complex business problems.

This role combines hands-on technical engineering, end-to-end project ownership, cloud deployment, and collaboration with UK-based stakeholders.

The ideal candidate will have demonstrable professional experience building Agentic AI solutions, strong machine learning fundamentals, and expertise in cloud infrastructure, MLOps, and production deployment.

Important: Hands-on professional experience building Agentic AI solutions is mandatory. Theoretical knowledge or academic exposure alone will not be sufficient.

Key Responsibilities

• Design, develop, and deploy advanced Agentic AI, NLP, and machine learning solutions to address measurable business requirements.
• Independently own technical workstreams, including solution architecture, milestones, implementation, delivery, and stakeholder communication.
• Develop scalable data pipelines and machine learning workflows using robust ETL, data modelling, security, and performance practices.
• Architect and deploy production-ready applications using cloud services, CI/CD pipelines, containerization, and MLOps frameworks.
• Conduct code reviews and guide team members on technical decisions, deployment standards, and engineering best practices.
• Present technical approaches, architectural trade-offs, project outcomes, and recommendations to clients and internal stakeholders.
• Collaborate with UK-based teams to ensure successful project delivery and alignment with business objectives.
• Maintain production systems and continuously improve model performance, reliability, and scalability.

Required Skills & Experience1. Agentic AI – Mandatory

• Demonstrable, hands-on professional experience developing Agentic AI solutions.
• Ability to explain the models, frameworks, tools, and architectures used in previous projects.
• Strong understanding of personal technical contributions, implementation approaches, and deployment outcomes.
• Experience building and delivering functional AI agent applications in real-world environments.

Theoretical exposure alone will not be considered sufficient.

2. Python, SQL & Machine Learning – Mandatory

• Strong proficiency in object-oriented Python and SQL.
• Applied experience with machine learning techniques, including:
• Forecasting
• Gradient Boosting
• Clustering
• Natural Language Processing (NLP)
• Bayesian Inference
• Familiarity with advanced data processing frameworks such as PySpark or Polars.

3. Cloud & DevOps – Mandatory

• Hands-on experience with at least two of the following cloud platforms:
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Experience deploying applications and managing cloud database services such as AWS RDS or Azure Cosmos DB.
• Working knowledge of Terraform, CI/CD pipelines, automated testing, and containerization.

4. MLOps – Mandatory

• Experience with machine learning orchestration and workflow automation.
• Familiarity with experiment tracking and hyperparameter tuning.
• Experience deploying and monitoring machine learning models.
• Understanding of automated model retraining pipelines and production ML lifecycle management.

5. Ownership & Communication – Mandatory

• Ability to work independently and manage technical delivery.
• Strong stakeholder management and project ownership skills.
• Excellent professional English communication skills.
• Confidence in explaining technical solutions, architectural decisions, and business impact.

6. Project Documentation – Mandatory

Candidates must have an updated resume clearly documenting:

• Relevant Agentic AI and machine learning projects.
• Specific AI models, frameworks, and tools used.
• Technology stack and architecture.
• Individual responsibilities and technical contributions.
• Implementation details and deployment experience.
• Measurable project outcomes and business impact.

All skills discussed during screening should also be reflected in the resume.

Educational Qualifications

Bachelor’s or Master’s degree in any relevant quantitative discipline, including:

• Computer Science
• Mathematics
• Statistics
• Physics
• Engineering
• Related quantitative fields

Preferred Qualifications

• Client-facing consulting experience.
• Experience with data quality management and project management.
• Familiarity with DVC and data versioning.
• Experience with PySpark or Ray.
• Exposure to serverless services such as AWS Lambda or Fargate.
• Experience with infrastructure automation tools such as Ansible or Terratest.
• Relevant Master’s degree or PhD.

Interview Process

Round 1: Coderbyte Assessment – 90 Minutes

Automated technical assessment.

Round 2: First Technical Interview – 30 Minutes

Technical discussion and live coding in a collaborative notebook.

Practice exercises:

• SQL: UK Weather Data
• Python: Log Analyser Tool

Round 3: Second Technical Interview – 60 Minutes

Experience Discussion – 30 Minutes:

• Project delivery and ownership.
• Solution design and architecture.
• ETL implementation.
• Security considerations.

Case Study – 30 Minutes:

• Architecture design.
• Security.
• Optimization.
• Technical rationale and trade-offs.

Round 4: Final Business Interview – 30 Minutes

• Business objectives and alignment.
• Communication and stakeholder engagement.
• Consulting mindset and culture fit.

Job DetailsParameterDetailsPositionSenior Data ScientistClientUK-based ClientCompanyArtefactExperience3–6 YearsOpenings4LocationPune, IndiaCompensation₹24–27 LPANotice Period60–90 DaysRelocationCandidates open to relocating to Pune are welcomeKey Skills

Agentic AI | Python | SQL | Machine Learning | NLP | Cloud Computing | AWS | Azure | GCP | MLOps | Terraform | CI/CD | PySpark | Polars | Docker | ETL | Data Modelling | Model Deployment | Stakeholder Management

Apply Now to work on advanced AI and machine learning solutions for a leading global consulting firm.

Pay: ₹2,400,000.00 - ₹2,700,000.00 per year

Experience:

• Data science: 4 years (Required)
• AI: 4 years (Required)
• Machine learning: 4 years (Required)
• MLOPS: 4 years (Required)
• Cloud development: 8 years (Required)

Work Location: In person