Data Scientist

Job Details:

Job Title: Specialist Data Science

Duration: Full Time (Direct Hire)

Location: Gurugram, IN

Position Title – Specialist Data Science

________________________________________

Role Purpose

The Specialist Data Science role is responsible for applying advanced analytical, statistical and machine learning techniques to extract insights from complex data and support evidence-based decision making across the organisation.

The role translates business questions and hypotheses into data science solutions, spanning data exploration, modelling, validation and insight communication. It ensures analytical outputs are robust, explainable, and aligned with enterprise standards for data quality, risk, privacy and responsible use.

The role works closely with data engineers, analytics engineers, product teams and business stakeholders to ensure data science solutions are fit-for-purpose, actionable and capable of being operationalised where required.

________________________________________

Key Responsibilities

• Analyse large, complex and diverse datasets to identify patterns, trends and insights relevant to business challenges.

• Design, develop, validate and maintain statistical, predictive and machine learning models for operational, tactical and strategic use.

• Apply appropriate modelling techniques and evaluation methods to ensure analytical robustness and transparency.

• Interpret and contextualise analytical results to support informed decision making.

• Collaborate with data engineers and platform teams to enable model deployment and reuse where required.

• Apply organisational standards for data quality, integrity, privacy, security and responsible use of AI throughout the analytics lifecycle.

• Assess data limitations, model bias, uncertainty and assumptions, and recommend appropriate mitigation strategies.

• Contribute to the development of reusable analytical assets, feature libraries and modelling approaches.

• Support experimentation, continuous improvement and innovation in data science practices.

• Engage and manage a range of internal stakeholders across technology, analytics and business domains.

• Identify and assess analytical and delivery risks and support a strong risk aware culture.

________________________________________

Key Deliverables

• Data analysis outputs, insights and recommendations aligned to defined business questions.

• Statistical, predictive and machine learning models with documented assumptions and limitations.

• Reusable analytical artefacts such as notebooks, features or modelling patterns.

• Visualisations, summaries and narratives that communicate insights clearly to stakeholders.

• Input into analytics solution design, experimentation outcomes and value assessments.

• Documentation supporting governance, assurance and knowledge reuse.

________________________________________

Skills and Capabilities

Data Science & Analytics

• Strong capability in data science, statistics and applied analytics.

• Ability to explore, analyse and model structured and unstructured datasets.

• Experience developing and evaluating statistical and machine learning models.

• Strong analytical reasoning and problem-solving skills.

Machine Learning & Advanced Analytics

• Practical experience applying machine learning techniques to real world problems.

• Understanding of model performance measures, validation techniques and limitations.

• Awareness of model lifecycle considerations, including monitoring and refresh.

Data Visualisation & Storytelling

• Ability to communicate complex analytical outcomes in a clear and compelling manner.

• Experience translating insights into actionable recommendations.

• Use of visualisation techniques to support understanding and decision-making.

Data Quality, Governance & Responsible Use

• Understanding of data quality, integrity and governance principles.

• Ability to identify data limitations, bias and uncertainty and incorporate controls.

• Awareness of responsible AI and ethical data practices.

Working with Delivery Teams

• Ability to collaborate effectively with data engineers, analytics engineers and product teams.

• Understanding of how analytical solutions integrate into broader analytics and technology ecosystems.

Professional & Behavioural Capabilities

• Strong stakeholder engagement and communication skills.

• Ability to explain analytical concepts to non technical audiences.

• Structured, evidence based approach to problem solving.

• High standard of written documentation and analytical rigour.

________________________________________

Experience and Qualifications

Experience

• Demonstrated experience in data science, advanced analytics or applied statistics roles.

• Experience applying analytical and machine learning techniques in complex environments.

• Proven ability to work across analytics, technology and business stakeholders.

• Experience operating within environments with data governance or risk controls is desirable.

Qualifications

Required

• Tertiary qualification (or equivalent experience) in data science, statistics, mathematics, engineering or a related discipline.

Desirable

• Postgraduate study or advanced training in data science or analytics.

• Experience with cloud-based analytics platforms.

• Exposure to MLOps, model monitoring or responsible AI practices.

________________________________________

Key Stakeholders

Internal

• Data and analytics teams.

• Data engineers and analytics engineers.

• Technology and platform teams.

• Risk, privacy and governance functions.

• Business product owners and operational leaders.

External

• Analytics and technology solution providers.

• Partners supporting analytics delivery or capability uplift.