Senior Data Scientist- ML Engineer @ SAP India

We help the world run better

Our company culture is focused on helping our employees enable innovation by building breakthroughs together. How We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences, values flexibility, and is aligned to our purpose-driven and future-focused work. We offer a highly collaborative, caring team environment with a strong focus on learning and development, recognition for your individual contributions, and a variety of benefit options for you to choose from.Apply now!

As a machine learning engineer what you'll do:

• Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architecture
• Use exceptional mathematical skills, in order to perform computations and work with the algorithms involved in this type of programming
• Collaborate with data engineers to build data and model pipelines
• Manage the infrastructure and data pipelines needed to bring code to production
• demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created
• Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production
• Use data modelling and evaluation strategy to find patterns and predict unseen instances
• Apply machine learning algorithms and libraries
• Lead on software engineering and software design
• Communicate and explain complex processes to people who are not programming experts
• Liaise with stakeholders to analyse business problems, clarify requirements and define the scope of the resolution needed
• Analyse large, complex datasets to extract insights and decide on the appropriate technique
• Research and implement best practices to improve the existing machine learning infrastructure
• Provide support to engineers and product managers in implementing machine learning in the product.

What you ll bring:

• Bachelors/Master s degree in computer science, machine learning, data science or related fields, with knowledge and experience on knowledge representation
• 8+ years of experience with atleast 3 projects or 5 years of hands on experience on data science or data engineering
• Proficiency in one or more programming languages, including Python, and knowledge of fundamental software engineering principles and NLP/machine learning design patterns
• Strong Skills in Relational Databases including database design, modeling, SQL and stored procedures
• Experience with Big Data processing and technologies especially Databricks, Py/Spark
• Experience and expertise working with data wrangling
• Strong problem-solving skills, business acumen, and demonstrated excellent oral and written communication skills with both technical and non-technical audiences
• Desired Skills Experience working with knowledge graph stores (Stardog, TigerGraph, Ontotext GraphDB, Neo4j) and surrounding semantic technology (OWL, RDF, SWRL, SPARQL, JSON-LD)

Meet your team :

We re a data analytics and decision science team that s part design studio, part research lab, part data factory. As such, big data analytics functions need business analysts, applied mathematicians, programmers and intelligent tech to support them. While most firms separate these into three distinct roles, we need them combined into one. You will join some of these highly valued individuals engaged in solving some of the most complex data science problems in the HR space.

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We build breakthroughs together

SAP innovations help more than 400,000 customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with 200 million users and more than 100,000 employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, we build breakthroughs, together.

We win with inclusion

SAP s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone regardless of background feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better and more equitable world.
SAP is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to the values of Equal Employment Opportunity and provide accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: hidden_email
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy . Specific conditions may apply for roles in Vocational Training.

EOE AA M/F/Vet/Disability:

Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, age, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability.
Successful candidates might be required to undergo a background verification with an external vendor.

Requisition ID: 378295 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid.

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