Immediate Hiring For Sr Data Scientist

Contactx Resource Management; Bengaluru; On-site; INR 2,400,000 - 3,600,000; Full time

Job summary

Contactx Resource Management invites a Senior Data & AI Scientist to lead the creation of production-grade AI and analytics solutions. You will guide multidisciplinary teams, mentor junior data scientists, and shape the team's technical direction.

You will design and deploy ML models, analyze large datasets, and translate insights to business outcomes. Strong Python expertise and collaboration are essential.

Qualifications

• Strong experience in ML, AI, and production-ready analytics.
• Experience leading projects and mentoring team members.
• Ability to communicate complex analytics to technical and non-technical audiences.
• Proficiency with Python and ML libraries.

Responsibilities

• Lead design, development, validation, and deployment of advanced AI/ML models.
• Explore modelling approaches to solving business problems.
• Collect, process, and analyze large datasets from multiple sources.
• Develop experimental models using Python and data science tooling.
• Translate findings into actionable business recommendations.
• Lead small teams in developing data science products.
• Collaborate with stakeholders to define analytical solutions.
• Ensure models are scalable, production-ready and governance-compliant.
• Mentor junior data scientists and support capability growth.
• Stay informed on AI/GenAI trends and opportunities.

Skills

Machine Learning

Python

GenAI

Leadership

Data Science

GCP

Statistical Modelling

Tools

GCP

Job description

Call on 9900913112

About the Opportunity

As a Senior Data & AI Scientist, you will play a leading role in developing advanced machine learning, AI, and analytics solutions that solve complex business challenges. You will work in multidisciplinary teams to explore problem statements, experiment with innovative approaches, and deliver production-ready solutions that create measurable business value. You will also provide technical leadership and coaching to junior data scientists while helping shape the technical direction of the team.

Key Responsibilities

• Lead the design, development, validation, and deployment of advanced AI and Machine Learning models.
• Explore and evaluate different modelling approaches to solve business problems.
• Collect, process, and analyse large and complex datasets from multiple sources.
• Develop experimental models and machine learning applications using Python and modern data science tooling.
• Perform complex statistical analysis and translate findings into actionable business recommendations.
• Lead small teams in the development, maintenance, and enhancement of data science products.
• Collaborate with business stakeholders, product owners, engineers, and analysts to define and deliver analytical solutions.
• Ensure models are scalable, production-ready, and compliant with governance standards.
• Mentor and coach junior data scientists and support capability development across the team.
• Stay informed on emerging AI, GenAI, machine learning, and data science trends and identify opportunities to apply them.

Required Skills & Experience

• Strong experience in Machine Learning, Predictive Analytics, Statistical Modelling, and AI.
• Expertise in Python and associated data science libraries.
• Experience in feature engineering, model selection, validation frameworks, and model performance evaluation.
• Strong understanding of supervised and unsupervised learning techniques.
• Experience working with cloud platforms, preferably Google Cloud Platform (GCP).
• Ability to communicate complex analytical findings to both technical and non-technical audiences.
• Experience leading projects and mentoring team members.
• Strong stakeholder management and collaboration skills.

Leadership Expectations

• Act as a technical leader within projects and workstreams.
• Drive adoption of best practices across Data Science and AI delivery.
• Support capability growth through coaching, mentoring, and knowledge sharing.
• Foster a culture of innovation, experimentation, and continuous improvement.

Typical Outcomes

• Industrialised AI and Machine Learning solutions delivering measurable business impact.
• Improved decision-making through advanced analytics and predictive modelling.
• Enhanced team capability through mentoring and technical leadership.
• Delivery of data science products aligned with governance, risk, and ethical AI standards.