Senior Decision Scientist

Birla Carbon; Thane; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Aditya Birla Group seeks a Senior Decision Scientist to lead the development and deployment of machine learning models addressing personalization, cross-sell, acquisition, retention, and risk modeling. You will mentor a team of data scientists and collaborate with cross-functional teams to deliver data-driven solutions.

The role involves handling large datasets, building data pipelines, and staying updated on industry trends to keep analytics competitive and innovative within the ABC Digital

Qualifications

• Bachelor's or Master’s degree in Mathematics, Statistics, Engineering, or equivalent quantitative field.
• 5–8 years of experience in data analysis or related roles in financial services or analytics.

Responsibilities

• Develop and implement ML models addressing business challenges including personalization, cross-sell, acquisition, retention, and risk modeling.
• Lead and mentor a team of data scientists and analysts; collaborate with cross-functional partners to deliver data-driven solutions.
• Manage data pipelines, data quality, and use external data sources to enrich analytics.

Skills

SQL

Python/PySpark

Machine learning

Leadership

Data analysis

Education

Bachelor's/Master's degree in Mathematics/Statistics/Engineering or quantitative disciplines

Tools

None

Job description

At the Aditya Birla Group, our Corporate Vision is aligned and intricately woven with our People Vision.

Senior Decision Scientist

Designation : NA

Job Description:

Job Purpose

This role is responsible to drive the development and implementation of machine learning models to address business challenges and drive personalization, cross-sell, acquisition, retention, and risk modeling. The job holder will collaborate with cross-functional teams to deliver data-driven solutions, while also managing and mentoring a team of data scientists and staying updated with industry trends and best practices in machine learning and data analysis.

Job Context/Job Challenges:Organizational Context ABC Digital has been incorporated as a wholly owned subsidiary of Aditya Birla Capital in 2023 to engage in distribution of Aditya Birla Capital products and providing services to customers, including web-based services, e-commerce, and payments facilities and allied activities. ABC Digital is developing an omni-channel based D2C platform (website and app) to acquire new customers and serve them seamlessly. In addition, ABC Digital has started a virtual engagement management through inbound and outbound calling. Also, ABC Digital is engaged in cross-selling different ABC products to walk-in branch customers. ABC Digital is collaborating with all ABCL subsidiaries to deliver a truly personalised and seamless omni-channel experience for both new and existing customers by building capacity and enhancing productivity through investments in talent, technology, marketing, and data and analytics. Key Challenges The biggest challenge is to compete in the new paradigm fintech where new competitors are making large investments from a long-term view, but ABC is making investments basis an annual break-even model. Moreover, our tech approach is traditional which creates a challenge in imagining and delivering innovative and agile tech solutions for new-age user experience. As ABCL does not manufacture any products and is not licensed to sell any products, the core challenge of the job is the dependence on businesses to give simple and relevant products with ‘3-click’ digital journeys to purchase these products. The dependence also extends to Call Centre desks to close the sale in cases where customers prefer to talk to an agent. Handling large and complex data sets can create challenges related to data quality, processing, and storage. The field of machine learning is constantly evolving, with new techniques and technologies emerging all the time. The Data Science team will need to stay up-to-date with industry trends and advancements in order to ensure that ABC Digital's data science capabilities remain competitive and innovative. Enabling Skill Sets & Qualifications Bachelor's/Master's degree in Mathematics/Statistics/Engineering or other quantitative disciplines 5-8 years of experience in data analysis or business analysis, in financial services Working knowledge of SQL & Python/PySpark. Extensive experience in handling large & complex datasets Experience in building and managing team of data scientists and data analysts Expertise in machine learning algorithms such as regression, decision trees, neural networks, clustering, NLP etc Strong communication and interpersonal skills to effectively collaborate with cross-functional teams including business stakeholders, data scientists, and developers. Attention to detail and ability to work in a fast-paced environment while managing multiple tasks simultaneously

Key Result Areas

KRA (Accountabilities) (Max 1325 Characters)

Supporting Actions (Max 1325 Characters)

KRA1 Data Management - Ensure all the data sets across all LOBs used by the data scientists for building analytical models are up to date and accurate so that the models in turn are of high and sustainable accuracy. Working with external data providers to build data pipelines to facilitate two-way data flow between our data warehouse and external systems – and working with IT to design and host this external data. Fix gaps in data ingest/quality by working with IT and business teams. Providing internal expertise to all members of the Central Analytics unit as the SME when it comes to data structures and mining.

KRA2 Cross-sell campaigns - Identifying the customers who are eligible for monthly cross-sell campaigns using internal and external data, based on product propensities, underwriting rules, etc. Ensuring accurate and timely campaign data flow from source to execution platforms (like tele sales dialers, campaign management systems for emails and SMSs, etc.) Maintaining campaign data governance to ensure data quarantines. Liaising with external data providers like credit bureaus, etc. for regular data enrichment scrubs.

KRA3 Dashboards Creating customer/business performance dashboards for tracking key KPIs like customer base, products per customer, upsell/cross-sell business, etc. for all LOBs.

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