As a Senior Manager for data science, data modelling & Analytics, you will lead a team of data scientists and analysts while actively contributing to the development and implementation of advanced analytics solutions. This role requires a blend of strategic leadership and hands-on technical expertise to drive data-driven decision-making across the organization.

Key Responsibilities

Hands-On Technical Contribution

• Design, develop, and deploy advanced machine learning models and statistical analyses to solve complex business problems.
• Utilize programming languages such as Python, R, and SQL to manipulate data and build predictive models.
• Understand end-to-end data pipelines, including data collection, cleaning, transformation, and visualization.
• Collaborate with IT and data engineering teams to integrate analytics solutions into production environments.
• Provide thought leadership on solutions and metrics based on the understanding of nature of business requirement.

Team Leadership & Development

• Lead, mentor, and manage a team of data scientists and analysts, fostering a collaborative and innovative environment.
• Provide guidance on career development, performance evaluations, and skill enhancement.
• Promote continuous learning and adoption of best practices in data science methodologies.
• Engage and manage a hierarchical team while fostering a culture of collaboration.

Strategic Planning & Execution

• Collaborate with senior leadership to define the data science strategy aligned with business objectives.
• Identify and prioritize high-impact analytics projects that drive business value.
• Ensure the timely delivery of analytics solutions, balancing quality, scope, and resource constraints.

Client Engagement & Stakeholder Management

• Serve as the primary point of contact for clients, understanding their business challenges and translating them into data science solutions.
• Lead client presentations, workshops, and discussions to communicate complex analytical concepts in an accessible manner.
• Develop and maintain strong relationships with key client stakeholders, ensuring satisfaction and identifying opportunities for further collaboration.
• Manage client expectations, timelines, and deliverables, ensuring alignment with business objectives.
• Develop and deliver regular reports and dashboards to senior management, market stakeholders and clients highlighting key insights and performance metrics.
• Act as a liaison between technical teams and business units to align analytics initiatives with organizational goals.

Cross-Functional Collaboration

• Work closely with cross capability teams such as Business Intelligence, Market Analytics, Data engineering to integrate analytics solutions into business processes.
• Translate complex data insights into actionable recommendations for non-technical stakeholders.
• Facilitate workshops and presentations to promote data driven conversations across the organization.
• Closely working with support functions to provide timely updates to leadership on operational metrics.

Governance & Compliance

• Ensure adherence to data governance policies, including data privacy regulations (e.g., GDPR, PDPA).
• Implement best practices for data quality, security, and ethical use of analytics.
• Stay informed about industry trends and regulatory changes impacting data analytics.

Qualifications

• Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Experience:
  • 12+ years of experience in advanced analytics, data science, data modelling, machine learning, Generative AI or a related field with 5+ years in a leadership capacity.
  • Proven track record of managing and delivering complex analytics projects.
  • Familiarity with the BFSI/Hi Tech/Retail/Healthcare industry and experience with product, transaction, and customer-level data
  • Experience with media data will be advantageous
• Technical Skills:
  • Proficiency in programming languages like Python, R, or SQL.
  • Experience with data visualization tools (e.g., Tableau, Power BI).
  • Familiarity with big data platforms (e.g., Hadoop, Spark) and cloud services (e.g., AWS, GCP, Azure).
  • Knowledge of machine learning frameworks and libraries.
• Soft Skills:
  • Strong analytical and problem-solving abilities.
  • Excellent communication and interpersonal skills.
  • Ability to influence and drive change within the organization.
  • Strategic thinker with a focus on delivering business outcomes.

Desirable Attributes

Proficient in the following advanced analytics techniques (Should have proficiency in most)

• Descriptive Analytics: Statistical analysis, data visualization.
• Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modelling
• Prescriptive Analytics: Optimization, simulation modelling.
• Text Analytics: Natural Language Processing (NLP), sentiment analysis.

Extensive knowledge of machine learning techniques, including (Should have proficiency in most)

• Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others
• Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others
• Reinforcement Learning: Q-learning, deep Q-networks, etc.

Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents (Good to Have)

• Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc.) for various objectives
• Hyper parameter tuning
• Prompt Engineering
• Embedding & Vectorization
• Fine tuning

Proficiency in data visualization tools such as Tableau or Power BI (Good to Have)

Strong skills in data management, structuring, and harmonization to support analytical needs (Must have)