Job Title: Data Scientist
Company: Deloitte
Location: Gurugram, Haryana, India
Description:
What impact will you make?




Every day, your work will make an impact that matters, while you thrive in a dynamic culture of inclusion, collaboration and high performance. As the undisputed leader in professional services, Deloitte is where you will find unrivaled opportunities to succeed and realize your full potentiaL




Deloitte is where you will find unrivaled opportunities to succeed and realize your full potential.




The Team

Deloitte’s practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning. Learn more about Analytics and Information Management Practice .




Job Title: Consultant Data ScientistReports To: Head of Data Science (Marketing) Division: Digital Data & Analytics

Role PurposeThe Data Science (Marketing) team is responsible for developing cutting-edge analytics and data science solutions that enable the design and execution of personalized customer communications across a range of channels. This includes both owned and paid media and covers existing customers and prospects. As a Lead Data Scientist, you will collaborate with business stakeholders, data scientists, data engineers, platform engineering, and architecture teams to drive business outcomes and advance Marketing's data science capabilities. A key focus will be building predictive models and event/trigger-based audiences by leveraging customer transaction data, behavioural signals, and demographics across online and offline sources.

Key Responsibilities

Lead the application of advanced analytics and machine learning across Marketing to drive strategic, data-informed decisions.
Design, build, and deploy predictive models and trigger-based audiences for use in Marketing communications across multiple media channels.
Enhance and manage feature engineering processes and feature store development for Marketing use cases.
Integrate digital analytics (e.g., Adobe Analytics) into data science models and use cases.
Deliver outcomes aligned with the AI/ML roadmap and architecture capabilities.
Continuously identify, promote, and embed new advanced analytics techniques within the team and across the Marketing function.
Present complex analytical findings in a clear and actionable manner using visualisation tools and insight presentations tailored to senior stakeholders.
Develop innovative analytic approaches to uncover unmet customer needs and improve financial wellbeing.
Champion standardisation and reusability of code, features, and solutions to improve time to insight.

Key Performance Indicators (KPIs)

Timely and high-quality delivery of data science solutions aligned to business goals.
Recognition as a key contributor to innovation and the development of Marketing analytics capabilities.
Measurable improvements in insight delivery timelines through standardized and reusable frameworks.
Strong stakeholder relationships; known as a trusted advisor within the business.

Essential Capabilities

Passion for analytics and data science, with awareness of the latest industry trends.
Proven ability to solve business problems using data and analytical techniques.
Strong strategic and customer-centric mindset.
Ability to communicate complex concepts clearly to non-technical stakeholders.
Strong problem-solving, documentation, and analytical thinking skills.
Self-management and accountability for personal tasks and project deliverables.
Collaboration and influencing skills across cross-functional teams.

Essential Experience

10+ years of experience in data science, analytics, or related fields.
Expertise in building, deploying, and operationalising machine learning models.
Proficiency in SQL, Python, PySpark, and Spark ML.
Hands-on experience with cloud platforms such as AWS (preferred), Azure, or GCP.
Skilled in using GitHub for version control and collaboration.
Strong experience in working with both structured and unstructured datasets.
Familiarity with Auto ML platforms such as Data Robot or H2O AI.
Deep understanding of customer and digital data, and their use in marketing and communications.
Experience with agile delivery methodologies and collaboration tools.

Desirable Experience

Leadership in the use of AI/ML and analytics to guide Marketing strategy.
Input into development of AI roadmaps and alignment with architecture/platform capabilities.
Ownership of continuous improvement in analytics tools, techniques, and adoption.
Skilled in visualising data using tools such as Tableau, Power BI, or similar.
Experience in developing innovative solutions that address both met and unmet customer needs.

Qualification Requirements

Bachelor’s or postgraduate degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or related disciplines.

Key Stakeholder Groups

Principal Data Scientist
Product Owners across the Marketing domain
Data Engineering (Marketing)




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