Principal Data Science Engineer

2 weeks ago

Hyderabad, Telangana, India Microsoft Full time

Overview

Are you a Data Science enthusiast with a knack for solving complex problems? Do you aspire to contribute to Microsoft's industry-leading Intelligent Supply Chain, enabling comprehensive visibility, insights, and optimization? We are seeking a Senior Data Scientist Manager with robust leadership, analytical, and communication skills to join our dynamic team.

The ideal candidate should possess profound expertise in machine learning and a passion for creating business value through the development of robust teams delivering AI-infused cloud-based solutions. They should be proficient at the end-to-end ML/AI solutions development process, from understanding the customer business problem to the production implementation of machine learning pipelines.

We are the Surface DASH team, committed to fostering a "culture of data" within the Surface organization. We welcome applications from proficient Data Science managers with a background in telemetry analysis and software/hardware development.

Our team explores a broad problem space, encompassing traditional software and hardware telemetry analysis, sentiment analysis, user behavior analysis, return analysis, manufacturing analysis, and more. We collaborate across E+D, striving to comprehend the complete customer experience with a Surface device. Our team plays a crucial role in linking our Hardware/Software/Firmware development teams to telemetry-based insights through pre-release device self-host data and in-market retail devices data. We believe in the power of telemetry to enable our strategy of delivering desirable and powerful devices.

Qualifications

REQUIRED QUALIFICATIONS

10+ years of experience developing and deploying end-to-end ML/AI systems. We prioritize those with a broad set of skills: working with structured and unstructured data, data processing at scale, feature engineering, and model operationalization. Bachelor's in computer science, Machine Learning, Data Science, or equivalent technical fields. Experience in leading a team and helping grow careers.

PREFERRED QUALIFICATIONS

Experience working within and directing geographically dispersed, diverse, and virtual teams. Experience managing both technical and non-technical stakeholders and able to resolve complex business and technical issues. We are looking for people who have broad Machine Learning experience across a variety of traditional and Deep Learning applications. Python skills, including the scientific Python stack, Machine Learning frameworks, and at least one major programming language such as C#. Demonstratable experience with software engineering principles, parallel and distributed computing, statistics, machine learning, cloud technologies like Azure, AWS, Google Cloud.

Responsibilities

Responsibilities

As part of our team, you will be working side-by-side with high-impact data scientists and strategic customers to solve complex problems. You will communicate trends and innovative AI solutions to stakeholders. You will work cross-functionally with several teams including engineering crews, product teams, and program management to deploy business solutions.

Our team prides itself on embracing a growth mindset, inspiring excellence, and encouraging everyone to share their unique viewpoints and be their authentic selves.

​

Business Understanding and Technical Oversight

Leads data-science projects or teams to align with business needs and deliver value. Defines and communicates the technical direction and strategy for the team and the project. This involves understanding the project goals, industry trends, and technical delivery context, guiding decision-making, ensuring a focused approach, and alignment with business objectives. Provide technical guidance, and suggest best practice, and drive team agreements related to best practices. Offers support to team members as and when required. Ensures the quality of the project deliverables is of the required standard. This involves creating clarity on expected standards, and overseeing the implementation to ensure they are adhered to.

Data Preparation and Understanding

Performs, and oversees, extensive exploratory data analysis on large and complex datasets to identify patterns, trends, and relationships, and ultimately generate high quality data and relevant hypotheses. This process involves applying statistical techniques such as hypothesis testing and regression analysis, as well as performing data cleaning, preprocessing, and addressing missing data, outliers, and anomalies to ensure high data quality and reliability.

Evaluation

Collaborate with stakeholders to understand the specific objectives and goals of project, and aid in designing a formal way of evaluating the systems' performance against these. This may involve identifying key performance indicators (KPIs) and metrics that align with the organization's objectives and identifying associations between these and the classical performance indications for models used in the system.

Industry and Research Knowledge/Opportunity Identification

Provides feedback, drives improvement, and shares knowledge as an Industry data science expert.

Coding and Debugging

Writes, reviews, and debugs code for complex projects and leads solution development.

Business Management

Leads data-science partnerships and IP improvement.

Customer/Partner Orientation

Provides customer-oriented insights and solutions by understanding the business, product, data, and customer perspective.

People Management

Managers deliver success through empowerment and accountability by modeling, coaching, and caring. Model - Live our culture; Embody our values; Practice our leadership principles. Coach - Define team objectives and outcomes; Enable success across boundaries; Help the team adapt and learn. Care - Attract and retain great people; Know each individual's capabilities and aspirations; Invest in the growth of others.

Responsible AI

Adheres to Microsoft's AI Customer Commitment

Culture and values

Embody Microsoft's culture and value as the foundation of how we operate Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect

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