Description: 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.

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: Bachelors or Masters 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 : Bengaluru