Principal Data Scientist

2 weeks ago

Bengaluru, India GSK Full time

**Site Name**: Bengaluru Luxor North Tower

**Posted Date**: Jan 12 2023
**Supply Chain** Data Analytics, Advanced AI team**:Principal** Data Scientist**

Given the increased focus on data and analytics, we need data scientists to work on cutting-edge AI/ML projects. For this reason, we are looking for a Principal Data Scientist to join our Advanced Analytics and Insights team.

In the emerging data and analytics world, AI/ML plays a key role, and the Principal Data Scientist must be a creative thinker and propose innovative ways to look at problems by using data. Expect our data to be messy and full of hidden treasures than only be found after using smart data wrangling and machine learning strategies. He/She will need to validate their findings using an experimental and iterative process along with continually being in dialogue with key business facing stakeholders for further validation. These approaches involve trial and error and may require multiple cycles, so are best addressed using iterative development methods such as agile or lean. Exciting projects involving manufacturing yield improvement, supply chain optimization, supply chain, quality control, and advanced process analytics are typical with effective collaboration between the Principal Data Scientist and the Subject Matter Experts being crucial to drive successful outcomes.

We expect the Principal Data Scientist to bring a wealth of experience delivering production level projects that understands the difficulties moving from POC to Data Product.

**Job Purpo**s**e**:
Principal Data Scientist is accountable for delivering projects with a high risk / reward ratio. He / She needs to ensure that they are focused on delivering value at optimal cost while ensuring that GSK Tech is looking far enough into the future to guide the business. You will help guide the team towards the optimal AI/ML strategies for the problems we are solving.

Accountable for all the business process identified in the scope below and contributing to the development of our AI/ML capabilities Strategy.
- Developing AI/ML projects and programs to deliver on time and avoid scope creep?
- Ensure the right level of AI/ML complexity is picked to solve business demands based on the knowledge and ability of the end users. Avoid overcomplicated solutions and drive for robust AI/ML solutions.
- Co-create with the business appropriate use-cases that will benefit from AI/ML.
- Strong software development standards using Devops/MLops.

Given the broad diversity and significant size of the information used as part of the analysis, assessing the validity of ML models can be challenging and, as such, the chances of misleading results are greater. As Principal Data Scientist you will need to be able to present back their findings to the business by exposing their assumptions and validation work in a way that can be easily understood by their business counterparts.

Business process areas in scope:

- Supply chain
- Manufacturing

**Key Re**s**pon**s**ibilitie**s**:

- Identify critical business problems and create analytical/modeling solutions while maintaining the right balance between speed to market and analytical soundness when designing solutions
- Influence machine learning strategy for a program/project; explores design options to assess efficiency and impact, develop approaches to improve robustness and rigour
- Lead discussions at peer review and uses quantitative skills to positively influence decision making
- Create algorithms to extract information from large, multiparametric data sets
- Work with our cross-functional team (data scientists, data engineers and research scientists) to define and deliver features in an iterative manner.
- Deploy -algorithms to production to identify actionable insights from large databases
- Compare results from various methodologies and recommend best techniques to stake holders
- Design, develop and implement analytical solutions using a variety of commercial and open source tools (common tools include Python, Git, TensorFlow, Keras, PyTorch, Databricks)
- Develop and embed automated processes for predictive model validation, deployment, and implementation
- Develop solutions using modern AI/ML stack like Feature Stores, Model Stores, and automated MLops.
- Make impactful contributions to internal discussions on emerging machine learning methodologies
- Educate the organization both from IT and the business perspectives on these new approaches, such as testing hypotheses and statistical validation of results
- Provide thought leadership: facilitate cross-geography fertilization of ideas and implements key principles/best-practices and guidelines across the categories
- Demonstrate a combination of business focus, strong analytical and problem-solving skills and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of the project and excellent written and communications skills to report back the findings in a

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