About Us:
As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers.
Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.
Overview about TII
At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.
Position Overview:
As Lead Data Scientist you will join a Data Sciences team responsible for creating highly personalised offers for our Guests. You will play crucial role in designing, implementing, and optimising highly scalable machine learning solutions in production.
Also, we expect you to guide the ML talent in the team on both algorithms and engineering. At an organizational level, you will conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need.
About You:
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Preferred MS or PhD in a quantitative field
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Experience with developing highly distributed ML systems
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8+ years of relevant experience in data science, analytics, or applied machine learning, with a strong track record of solving complex business problems through data-driven approaches.
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Demonstrated ability to translate business problems into analytical solutions, leveraging statistical, machine learning, or optimization techniques to drive business impact.
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Proven experience in designing, building, and deploying machine learning models and pipelines in production environments at scale.
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Collaborate cross-functionally with data engineers, product managers, and software engineers to define problem statements, design experiments, and build data solutions that deliver measurable value.
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Strong programming skills in Python or Java, with hands-on experience using big data technologies such as Hadoop or Spark. Familiarity with machine learning libraries and frameworks like TensorFlow, PyTorch, or Keras is a plus.
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Ability to communicate complex technical concepts and results clearly to both technical and non-technical stakeholders, using visualizations, dashboards, and storytelling techniques.
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Proactive and results-oriented, capable of driving projects independently and delivering under tight deadlines.
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A collaborative team player with experience working across global teams and contributing to a shared vision.
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Demonstrated experience in mentoring junior data scientists or analysts, fostering a culture of learning and innovation.
Know More About us here:
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Life at Target- https://india.target.com/
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Benefits- https://india.target.com/life-at-target/workplace/benefits
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Culture- https://india.target.com/life-at-target/belonging
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What We Do
Target is an American retailing company providing access to a wide selection of products such as furniture, electronics, toys, and more.
Target is one of the world’s most recognized brands and one of America’s leading retailers. We make Target our guests’ preferred shopping destination by offering outstanding value, inspiration, innovation and an exceptional guest experience that no other retailer can deliver. Target is committed to responsible corporate citizenship, ethical business practices, environmental stewardship and generous community support. Since 1946, we have given 5 percent of our profits back to our communities. Our goal is to work as one team to fulfill our unique brand promise to our guests, wherever and whenever they choose to shop.
