Senior Manager Data Science, Data Modelling And Analytics Job in Merkle B2b

Job Title: Senior Manager Data Science, Data Modelling & Analytics

Location: Bengaluru

Department: Insights & Analysis

About the Role:

As a Senior Manager, you will lead a team of data scientists and analysts, driving the development and deployment of advanced analytics solutions that enable data-driven decision-making. This role blends strategic leadership with hands-on technical expertise, playing a critical part in delivering impactful insights and analytics across the organization.

Key Responsibilities:

Hands-On Technical Contribution:

• Design, develop, and deploy advanced machine learning models and statistical analyses to address complex business challenges.
• Utilize Python, R, SQL, and other tools to manipulate data and build predictive models.
• Manage end-to-end data pipelines including collection, cleaning, transformation, and visualization.
• Collaborate with IT and data engineering teams to integrate analytics solutions into production environments.
• Provide thought leadership on analytics solutions and metrics aligned with business needs.

Team Leadership & Development:

• Lead, mentor, and manage a team of data scientists and analysts, fostering collaboration and innovation.
• Guide career development, conduct performance evaluations, and promote skill enhancement.
• Encourage continuous learning and adoption of best practices in data science methodologies.

Strategic Planning & Execution:

• Collaborate with senior leadership to define and execute data science strategy aligned with business goals.
• Identify and prioritize high-impact analytics projects that deliver business value.
• Ensure timely and quality delivery of analytics solutions balancing scope and resources.

Client Engagement & Stakeholder Management:

• Act as primary point of contact for clients, translating business challenges into data science solutions.
• Lead client presentations, workshops, and discussions, effectively communicating complex analytical concepts.
• Build and maintain strong client relationships, managing expectations and deliverables.
• Deliver regular reports and dashboards to senior management and stakeholders.
• Bridge communication between technical teams and business units to align analytics initiatives with organizational objectives.

Cross-Functional Collaboration:

• Work closely with Business Intelligence, Market Analytics, and Data Engineering teams to integrate analytics into business processes.
• Translate complex insights into actionable recommendations for non-technical stakeholders.
• Facilitate data-driven workshops and presentations across the organization.
• Collaborate with support functions to provide timely leadership updates on operational metrics.

Governance & Compliance:

• Ensure compliance with data governance policies and data privacy regulations (e.g., GDPR, PDPA).
• Implement best practices for data quality, security, and ethical analytics use.
• Stay abreast of industry trends and regulatory changes affecting data analytics.

Qualifications:

Education:

• Bachelor s or Master s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.

Experience:

• 12+ years in advanced analytics, data science, data modelling, machine learning, or related fields.
• 5+ years in leadership roles managing analytics teams and projects.
• Experience in BFSI, Hi-Tech, Retail, or Healthcare industries preferred.
• Experience with media data is a plus.

Technical Skills:

• Proficiency in Python, R, SQL.
• Experience with data visualization tools like Tableau, Power BI.
• Familiarity with big data platforms (Hadoop, Spark) and cloud services (AWS, GCP, Azure).
• Strong knowledge of machine learning frameworks and libraries.

Soft Skills:

• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal abilities.
• Ability to influence and drive organizational change.
• Strategic thinker focused on business outcomes.

Desirable Expertise:

Advanced Analytics Techniques:

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

Machine Learning Techniques:

• Supervised Learning: Linear/logistic regression, decision trees, random forests, gradient boosting, SVMs.
• Unsupervised Learning: Clustering, PCA, anomaly detection.
• Reinforcement Learning: Q-learning, deep Q-networks.

Generative AI & Large Language Models (Good to Have):

• Experience with GPT, Gemini, LLAMA, etc. for text generation, summarization, conversational agents.
• Hyperparameter tuning, prompt engineering, embeddings, fine-tuning.

Additional Skills:

• Proficiency with Tableau or Power BI (advanced visualization).
• Strong data management, structuring, and harmonization skills.