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Senior Data Scientist

Aditi Consulting

Cincinnati, OH

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JOB DETAILS
SALARY
$63.90–$64.60 Per Hour
SKILLS
A/B Testing, Analysis Skills, Artificial Intelligence (AI), Automotive Automation, Best Practices, Cloud Computing, Communication Skills, Comparative Analysis, Consulting, Customer Experience, Customer/Client Research, Data Analysis, Data Modeling, Data Science, Deep Learning, Demographics, Detail Oriented, Diversity, Experiment Design, GCP (Good Clinical Practices), Large-Scale Systems, Machine Learning, Messaging Technology, Metrics, Microsoft Windows Azure, Model Review, Performance Analysis, Problem Solving Skills, Purchasing/Procurement, Python Programming/Scripting Language, Reporting Dashboards, Retail, Root Cause Analysis, SQL (Structured Query Language), Short Messaging Service (SMS), Speech Technology, State Laws and Regulations, Statistics, Support Documentation, Systems Maintenance, Technical Support, Telephony, Training/Teaching, eCommerce
LOCATION
Cincinnati, OH
POSTED
1 day ago
Payrate: $63.90- $64.60/hr.
 
Summary:
Senior Data Scientist, Relevancy Team – Personalization & Loyalty Strategy Relevancy Team is responsible for making relevant and personalized customer experiences for E-commerce site, which ranks among the top 10 ecommerce companies. We deliver trillions of recommendations to the website on a scale and make them available to millions of customers. The team has a rich portfolio of sciences which include product and coupon recommender systems, substitute recommendations, and shoppable recipes. We are seeking a talented and experienced senior data scientist to join our data science team, specializing in building search and recommender systems. The ideal candidate will have proven track record of developing deep learning models, expertise in ML frameworks such as TensorFlow or PyTorch, and a strong understanding of various recommendation models and techniques.
 
Responsibilities:
  • Design, develop, and implement recommender systems tailored to grocery retail and e-commerce personalization needs.
  • Build advanced machine learning and deep learning models to deliver personalized products, coupons, substitutes, and recipe recommendations.
  • Define evaluation methods and key metrics to measure recommender system performance and identify areas for improvement.
  • Conduct A/B testing and offline model evaluations to compare recommendation strategies and improve model outcomes.
  • Perform root cause analysis and model interpretability reviews to understand recommendation results and improve accuracy.
  • Improve personalization by incorporating customer preferences, dietary needs, shopping behaviors, and engagement patterns.
  • Explore recommendation diversity strategies that expose customers to a broader range of relevant products while maintaining accuracy.
  • Partner with ML engineers to support model deployment, serving, versioning, and production pipeline best practices.
  • Collaborate with data scientists, data engineers, full stack engineers, product teams, and business stakeholders to deliver data science solutions.
  • Integrate transactional, customer, product, demographic, and user feedback data to support model development and analytics.
  • Build customer analytics pipelines, reporting dashboards, and performance tracking to monitor recommendation effectiveness over time.
  • Document best practices, technical insights, lessons learned, and model development approaches for internal knowledge sharing.
  • Contribute to internal tools, libraries, and documentation that support adoption and maintenance of recommender system solutions.
  • Participate in knowledge-sharing sessions and technical discussions to support continuous learning across the team.
 
Requirements
  • 2+ years of proven experience building deep learning models for large-scale recommender systems.
  • Proficiency in ML frameworks such as TensorFlow or PyTorch.
  • Proficiency in SQL, Python and Spark for data analysis and manipulation. Experience working with Databricks is a plus.
  • Proficiency with statistics, design of experiments, exploration data analysis, and insights generation.
  • Experience working with cloud platforms like Azure or GCP.
  • Experience working with Data Engineering and MLOps is desirable.
  • High level of independence to develop and own toolkits, pipelines, and dashboards.
  • Excellent problem-solving skills and a proactive approach to addressing challenges.
  • Strong analytical and critical thinking skills with attention to detail.
  • Prior experience in the retail or e-commerce industry is a plus.
  • Must be able to learn from others and teach others and work collaboratively as part of a highly interdependent team.
  • Ability to communicate complex ideas effectively to both technical and non-technical stakeholders.
 
Pay Transparency: The typical base pay for this role across the U.S. is: $63.90- $64.60/hour. Non-exempt positions are eligible for overtime at a rate of 1.5 times the base hourly rate for all hours worked in excess of 40 in a work week, or as required by state or local law. Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education and experience. Full-time employees are eligible to select from different benefits packages. Packages may include medical, denmatch, lifeion benefits, health savings accounts with qualified medical plan enrollment, 10 paid days off, 3 days paid bereavement leave, 401(k) plan participation with employer match,  life and disability insurance, commuter benefits, dependent care flexible spending account, accident insurance, critical illness insurance, hospital indemnity insurance, accommodations and reimbursement for work travel, and discretionary performance or recognition bonus. Sick leave and mobile phone reimbursement provided based on state or local law. 
 
Consent to Communication and Use of AI Technology: By submitting your application for this position and providing your email address(es) and/or phone number(s), you consent to receive text (SMS), email, and/or voice communication whether automated (including auto telephone dialing systems or automatic text messaging systems), pre-recorded, AI-assisted, or individually initiated from Aditi Consulting, our agents, representatives, or affiliates at the phone number and/or email address you have provided. These communications may include information about potential opportunities and information. Message and data rates may apply. Message frequency may vary.
You represent and warrant that the email address(es) and/or telephone number(s) you provided to us belong to you and that you are permitted to receive calls, text (SMS) messages, and/or emails at these contacts. You also acknowledge and agree to Aditi Consulting LLC’s use of AI technology during the sourcing process, including calls from an AI Voice Recruiter. AI is used solely to gather data and does not replace human-based decision-making in employment decisions. Calls may be recorded.
 
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