Data Science Lead Consultant - Lyon [H/F/D]

Role Summary

We are looking for candidates to build and implement analytics solutions to our esteemed clients. The incumbent should have strong aptitude for numbers, experience in any domain and willingness to learn some cutting‑edge technologies.

Roles & Responsibilities

• Understand the requirements from the business and translate them into appropriate technical requirements.
• Creating a detailed business analysis, outlining problems, opportunities and solutions for a business.
• Perform activities related to data wrangling, model building and model deployment.
• Stay current with the latest research and technology and communicate your knowledge throughout the enterprise.
• Lead initiatives to improve the team morale, camaraderie, and collaboration.

Technical Skills

Must Have Skills (Data Science/Machine Learning):

• Hands‑on experience in Data Science, Python/R, PySpark/SparkR coding and associated state‑of‑the‑art technologies for exploratory data analysis, building predictive models with big data. Familiarity with standard clustering, classification, dimensionality reduction and other techniques/algorithms in machine learning.
• Experience in building and implementing ML‑driven business transformation use cases such as demand forecasting, price/promo optimization, etc.
• SQL knowledge and experience working with relational databases.
• Hands‑On MS Azure/GCP/AWS cloud, Databricks/Snowflake, SQL knowledge.
• Scaling ML models from POC phase.
• List Azure services required for deployment, Azure Databricks and Azure DevOps setup.
• Ability to communicate actionable insights using data, often to a non‑technical audience.
• Ability to drive end‑to‑end data‑driven solutions with excellent sense of risk and resource management in any given situation.
• Good knowledge on statistical concepts such as properties of distributions, statistical tests and their proper usage.
• Analyze and extract relevant information from large amounts of data to help in automating solutions and optimizing key processes.
• A quick and enthusiastic learner (must) and who is willing to work on new technologies depending on requirement.

Must Have Skills (Machine Learning Operations / Machine Learning Engineer):

• Object‑oriented programming, coding standards, architecture & design patterns, configuration management, package management, logging, documentation.
• Experience in Test‑Driven Development and using Pytest frameworks, Git version control, REST APIs.
• Azure ML best practices in environment management, run‑time configurations (Azure ML & Databricks clusters), alerts.
• Experience designing and implementing ML systems & pipelines, MLOps practices and tools such as MLFlow, Kubernetes, etc.
• Exposure to event‑driven orchestration, online model deployment.
• Contribute towards establishing best practices in MLOps system development.
• Proficiency with data analysis tools (e.g., SQL, R & Python).
• High level understanding of database concepts/reporting & data science concepts.
• Hands‑on experience working with client IT/Business teams in gathering business requirements and converting them into requirements for the development team.
• Experience managing client relationships and developing business cases for opportunities.
• Azure AZ‑900 certification with Azure architecture understanding is a plus.
• Expertise in object‑oriented Python programming with 4–5 years’ experience.
• DevOps working knowledge with implementation experience – 1 or 2 projects at minimum.
• Hands‑On MS Azure / GCP / AWS cloud knowledge.
• Help team with ML pipelines from creation to execution.
• List Azure services required for deployment, Azure Databricks and Azure DevOps setup.
• Assist team with coding standards (flake8, etc.).
• Guide team to debug issues with pipeline failures.
• Engage with business / stakeholders with status updates on progress of development and issue fixes.
• Automation, technology and process improvement for deployed projects.
• Setup standards related to coding, pipelines and documentation.
• Adhere to KPI / SLA for pipeline run, execution.
• Research new topics, services and enhancements in cloud technologies.

Other key to have Skills

• Understanding of any one domain (e.g., Retail, Supply chain, Logistics, Manufacturing).
• Understanding of the project lifecycles: waterfall and agile.

Soft Skills

• Strong verbal and written communication skills with the ability to work well in a team.
• Strong customer focus, ownership, urgency and drive.
• Ability to handle multiple, competing priorities in a fast‑paced environment.
• Work well with team members to maintain high credibility.

Work Experience

• Having 10+ years of experience in Data Analytics, Data Science and Machine Learning, Machine Learning deployments.
• Flexible to travel.

Infosys is proud to be an equal opportunity employer.