Senior Manager – Data science, data modelling and analytics

Job Description:

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)

Location:

Brand:

Time Type:

Contract Type: