Lead Data Scientist
<p><span><b>Our Purpose</b></span></p><p></p><p><i>Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.</i></p><p></p><p><b>Title and Summary</b></p><h3></h3><p></p>Lead Data Scientist<h3></h3><p style="text-align:inherit"></p>Overview:<br><br>We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. <br><br>Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results. <br><br>The Lead Data Scientist is responsible for developing, deploying, and monitoring Data Science solutions that involve Machine Learning, Deep Learning, and other AI techniques.<br><br>Responsibilities:<br><br>1. Transform business challenges into scientific research problems <br>2. Develop data-driven solutions to address business challenges using appropriate techniques (AI, ML, DL, etc.)<br>3. Build and execute various data science projects for product and business use cases across the Ethoca organization (both product and technology).<br>4. Hands on data extraction, data analysis, data cleaning, preparation, modeling, and evaluation<br>5. Deploy, document, maintain and monitor the developed solutions<br>6. Presenting data science results to a variety of audience<br>7. Protect the developed algorithms and solutions by patenting the technology and consider publishing at academic and industrial research conference.<br>8. Build prototypes and proof-of-concepts and conduct tool evaluations.<br>9. Knowledge dissemination by presenting work externally at conferences and Universities.<br>10. Collaborate with internal teams and across other Mastercard teams<br><br>All about You:<br><br>1. Substantial experience in developing and deploying Machine learning and Deep learning solutions end-to-end (data exploration to deployment). Will consider even 3+ years if candidate has a Ph.D. from relevant areas.<br>2. Deep understanding of different Machine learning, Deep learning, and AI algorithms and the math behind it.<br>3. Strong scientific communication skills.<br>4. Handling data responsibly by maintaining data governance, privacy, and ring-fencing standards<br>5. Curious, Critical thinker, good hacking skills and scientific reasoning.<br>6. Not afraid to ask questions and propose new ideas<br>7. Master’s in computer science or quantitative field is a must and PhD is good to have.<br><br>Skills:<br><br>Python, R Programming<br>ML Frameworks (Scikit learn) and Deep Learning Framework (TensorFlow, PyTorch)<br>SQL, SAP HANA, Hadoop, Snowflake databases<br>Linux, Azure environment, Azure Machine Learning, and Databricks <br><br>Nice to have:<br><br>1. In addition to the above, identify new challenges that can be solved using the data.<br>2. Generate new innovative ideas that can potentially add value to the organization.<h3></h3><p style="text-align:inherit"></p>Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.<h3></h3><p style="text-align:inherit"></p><p style="text-align:left"><b>Corporate Security Responsibility</b></p><p style="text-align:left"><br />All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:</p><ul><li><p style="text-align:left">Abide by Mastercard’s security policies and practices;</p></li><li><p style="text-align:left">Ensure the confidentiality and integrity of the information being accessed;</p></li><li><p style="text-align:left">Report any suspected information security violation or breach, and</p></li><li><p style="text-align:left">Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.</p></li></ul><p style="text-align:inherit"></p><p style="text-align:inherit"></p><h3></h3><p style="text-align:inherit"></p>In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program. This posting reflects one or more current openings on our team.<p style="text-align:inherit"></p><p style="text-align:left"><b>Pay Ranges</b></p>Toronto, Canada: $127,000 - $203,000 CAD<h3></h3><p style="text-align:inherit"></p><h3></h3><p style="text-align:inherit"></p><h3></h3><p style="text-align:inherit"></p><h3></h3><p style="text-align:inherit"></p>
