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Are you ready to make an impact at DTCC? Do you want to work on innovative projects, collaborate with a dynamic and supportive team, and receive investment in your professional development? At DTCC, we are at the forefront of innovation in the financial markets. We're committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact. We foster a thriving internal community and are committed to creating a workplace that looks like the world that we serve. Pay And Benefits Competitive compensation, including base pay and annual incentive Comprehensive health and life insurance and well-being benefits Pension Paid Time Off and Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being. DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays and a third day unique to each team or employee). The Impact You Will Have In This Role Being a member of the Technology Research and Innovation team, you will help advance DTCC’s ability to explore, validate, and productize emerging data science, machine learning, AI, and GenAI capabilities that create measurable value across the organization. This role sits at the intersection of research, applied machine learning, data engineering, and product development, with a strong focus on moving ideas beyond experimentation into scalable, production-ready solutions. The Principal Data Scientist / Machine Learning Engineer will design and deliver practical, production-oriented solutions in a financial services environment where governance, risk, controls, reliability, and business adoption are critical. This is not a purely theoretical research role; the ideal candidate will have demonstrated experience taking data science, machine learning, AI, or GenAI concepts from ideation through prototype, validation, productization, and deployment while partnering closely with product owners, technology teams, business stakeholders, and innovation leaders to rapidly develop solutions, test feasibility, define a path to production, and align technical work to real business outcomes. Your Primary Responsibilities Champion Python-Centric Data Engineering: Spearhead the adoption and optimization of Python for data engineering tasks, including data ingestion, transformation, and advanced analytics. Guide team in leveraging Python libraries and frameworks to build scalable, maintainable solutions Architect Data Pipeline Solutions: Strategically design and implement enterprise-grade data pipelines for optimal data processing thru python and Snowflake. Establish standards for data quality, security, and integrity, and ensure seamless integration of disparate data sources and formats Strategic Cross-Functional Collaboration: Partner with technology teams to identify opportunities for leveraging data and analytics. Translate business requirements into technical solutions and ensure that insights are actionable and aligned with organizational objectives Lead Advanced Machine Learning Initiatives: Direct the design, development, and deployment of robust machine learning models using Python, guiding teams in data preprocessing, feature engineering, model optimization, and evaluation. Oversee the application of advanced techniques, including deep learning, regression, classification, and clustering, to solve high-impact business problems Demonstrate accountability by taking ownership of solution ideation, development, and execution, including coordinating efforts with internal and external teams/stakeholders to present the results (reports and presentations) in a clear and concise manner Technical Leadership and Mentorship: Provide guidance and technical leadership to junior engineers, create high-performance and reusable approaches to solve challenging problems, and cultivate a culture of excellence, continuous learning, and innovation Risk Management and Compliance: Integrate risk and control processes into all data engineering activities, proactively monitor for potential issues, and escalate risks as appropriate to ensure compliance with organizational standards NOTE: The Primary Responsibilities of this role are not limited to the details above. Qualifications Minimum 8 years of related experience Bachelor's degree (preferred) or equivalent experience Talents Needed For Success Extensive experience in data engineering and machine learning model development using Python Proven expertise in architecting data pipelines with Python and Snowflake Strong leadership and mentorship skills, with experience managing and developing technical teams Excellent communication and collaboration abilities Sound understanding of data governance and risk management Experience in Financial industry is preferred Experience in Data Visualization tools is a plus We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.