Senior Data Scientist

Year    KA, IN, India

Job Description

Who We Are:



Saks Global is a combination of world-class luxury retailers, including Neiman Marcus, Bergdorf Goodman, Saks Fifth Avenue and Saks

OFF 5TH, as well as a portfolio of prime U.S. real estate holdings and investments. Saks Global is deeply committed to helping luxury

consumers discover the most sought-after established and emerging brands from around the world. Powered by data-driven technology

and centered on the customer, Saks Global is on a mission to redefine the luxury shopping experience through highly personalized

service, with greater opportunities for product discovery across all channels.



Role Summary:



Central to Saks' customer-centric marketing strategy is our Customer DNA. The successful candidate will be a highly independent and business-savvy Senior Data Scientist to lead the development and execution of advanced analytics that drive measurable business impact. The ideal candidate will demonstrate strong ownership of projects, from framing business problems to delivering actionable recommendations. They will support Saks strategies through the delivery of best-of-breed campaign management, measurement of all-channel and cross banner marketing promotions, the extraction of key analytical insights and by providing customer centric recommendations -- spanning both store and e-commerce channels. The ability to think strategically about customer and business challenges and proactively propose solutions will be critical to their success. Forward thinking is the key to this role as new technologies and opportunities present themselves.



Key Qualifications:



5+ years of demonstrated ability in a similar data scientist role

Bachelor's degree in data science, computer science, statistics, economics,

mathematics, or a similar quantitative field; Master's Degree preferred

Comprehensive experience with ML and AI modeling, especially in product

recommendation algorithms and NLP. Proven track record of teaming up with data

engineers for large-scale ML tool production

Proficient programming skills in relevant languages/tools (Python, SQL, Spark, Git &

Github, AWS EMR, Airflow, AWS SageMaker, Dataiku, or similar platforms)

Ability to apply the ML/AI modeling approaches/classes of algorithms to business

problems e.g., regressions, Random Forest, GBM, Neural Networks, boosted trees,

LDA, collaborative filtering, etc.

Strong business acumen and knowledge of retail business and digital marketing

Excellent communication skills and value in building solid relationships cross-functionally

to capture business needs and translate them into actionable project plans to influence

real-world marketing applications or decisions



Role Description:



Lead the strategic development of data-driven solutions within areas such as business

forecasting, product analytics, and targeted marketing. This includes designing and

implementing data pipelines, developing analytical frameworks, and creating models that

directly influence business decisions

Manage end-to-end data science projects, from defining objectives and scope, to

delivering actionable insights and recommendations. Ensure clear communication of

project status, findings, and implications to business stakeholders

Contribute to Product DNA data project to support merchandising and buying decisions

Conduct ad-hoc analyses using customer, merchandising, operational, and

macroeconomic data to support various Saks initiatives and deliver actionable insights to

different functional teams



Develop and automate analytical processes for generating customer profiles, creating

targeted campaign lists, and performing post-campaign evaluations. Ensure that insights

are actionable and directly applicable to marketing and CRM strategies

Team up with Data Architects, Data Engineers, MLops Engineers, and other company

players to conceive and execute data pipelines crucial for our personalization objectives

Stay informed on the latest industry trends and advancements in data science, machine

learning, and AI, incorporating new techniques and technologies as appropriate

Drive research and methodology development for machine learning use cases in product

recommendation, customer journey optimization, and conversion enhancement.

Gather business requirements for critical blind spots in business processes such as

access to customer information, and design an application that is marketer-friendly but

solves data gaps and consumes data science models for end-user applications



Your Life and Career at Saks:



Exposure to rewarding career advancement opportunities

A culture that promotes a healthy, fulfilling work/life balance



Benefits package for all eligible full-time employees (including medical, vision and dental).



Thank you for your interest in Saks. We look forward to reviewing your application.



Saks provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability

or genetics. In addition to federal law requirements, Saks complies with applicable state and local laws governing nondiscrimination in employment in every location in which

the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer,

leaves of absence, compensation and training.

Saks welcomes all applicants for this position. Should you be individually selected to participate in an assessment or selection process, accommodations are available upon

request in relation to the materials or processes to be used.



Saks.com is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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Job Detail

  • Job Id
    JD3924765
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    KA, IN, India
  • Education
    Not mentioned
  • Experience
    Year