Job Title: Senior Data Scientist Location: Columbus OH/ Pittsburg PA/ Richmond VA/ Louisville KY/ Charleston WV. Long term Contract Can do Only W2 No C2C
Job Summary:
We are seeking a highly skilled Senior Data Scientist Recommender Systems to support a large-scale retail/e-commerce personalization initiative.
The ideal candidate will have strong expertise in deep learning-based recommendation systems large-scale machine learning model development and production-grade ML solutions.
This role requires hands-on experience building recommendation engines conducting experimentation and collaborating with cross-functional teams to deliver personalized customer experiences.
Key Responsibilities:
Design and develop advanced recommender systems for retail and e-commerce personalization.
Build machine learning and deep learning models for product coupon and content recommendations.
Define KPIs evaluation metrics and model performance tracking frameworks.
Conduct A/B testing and offline model evaluations to measure recommendation effectiveness.
Improve personalization strategies using customer behavior and preference data.
Develop scalable pipelines for recommendation systems and large-scale model processing.
Collaborate with ML Engineers Data Engineers Product Managers and business stakeholders.
Support deployment monitoring versioning and lifecycle management of ML models.
Build dashboards and analytical reports for model performance tracking.
Document model architecture technical best practices and key learnings.
Communicate complex machine learning concepts to technical and non-technical stakeholders.
Required Skills:
Strong proficiency in Python and SQL.
Minimum 2 years of experience with Deep Learning-based Recommender Systems.
Experience building production-grade recommendation systems.
Hands-on experience with large-scale machine learning model development.
Experience with Spark for large-scale data processing.
Strong expertise in TensorFlow or PyTorch.
Experience with cloud platforms such as Azure or Google Cloud Platform (GCP).
Strong understanding of Statistics A/B Testing and Experimentation Design.
Excellent communication and stakeholder collaboration skills.
Preferred Qualifications
Experience with Databricks.
Exposure to Data Engineering and MLOps practices.
Experience in Retail or E-commerce domains.
Experience with scalable ML pipelines and model deployment frameworks.
Knowledge of model monitoring and versioning methodologies.
Job Title: Senior Data Scientist Location: Columbus OH/ Pittsburg PA/ Richmond VA/ Louisville KY/ Charleston WV. Long term Contract Can do Only W2 No C2C Job Summary: We are seeking a highly skilled Senior Data Scientist Recommender Systems to support a large-scale retail/e-commerce personaliz...
Job Title: Senior Data Scientist Location: Columbus OH/ Pittsburg PA/ Richmond VA/ Louisville KY/ Charleston WV. Long term Contract Can do Only W2 No C2C
Job Summary:
We are seeking a highly skilled Senior Data Scientist Recommender Systems to support a large-scale retail/e-commerce personalization initiative.
The ideal candidate will have strong expertise in deep learning-based recommendation systems large-scale machine learning model development and production-grade ML solutions.
This role requires hands-on experience building recommendation engines conducting experimentation and collaborating with cross-functional teams to deliver personalized customer experiences.
Key Responsibilities:
Design and develop advanced recommender systems for retail and e-commerce personalization.
Build machine learning and deep learning models for product coupon and content recommendations.
Define KPIs evaluation metrics and model performance tracking frameworks.
Conduct A/B testing and offline model evaluations to measure recommendation effectiveness.
Improve personalization strategies using customer behavior and preference data.
Develop scalable pipelines for recommendation systems and large-scale model processing.
Collaborate with ML Engineers Data Engineers Product Managers and business stakeholders.
Support deployment monitoring versioning and lifecycle management of ML models.
Build dashboards and analytical reports for model performance tracking.
Document model architecture technical best practices and key learnings.
Communicate complex machine learning concepts to technical and non-technical stakeholders.
Required Skills:
Strong proficiency in Python and SQL.
Minimum 2 years of experience with Deep Learning-based Recommender Systems.
Experience building production-grade recommendation systems.
Hands-on experience with large-scale machine learning model development.
Experience with Spark for large-scale data processing.
Strong expertise in TensorFlow or PyTorch.
Experience with cloud platforms such as Azure or Google Cloud Platform (GCP).
Strong understanding of Statistics A/B Testing and Experimentation Design.
Excellent communication and stakeholder collaboration skills.
Preferred Qualifications
Experience with Databricks.
Exposure to Data Engineering and MLOps practices.
Experience in Retail or E-commerce domains.
Experience with scalable ML pipelines and model deployment frameworks.
Knowledge of model monitoring and versioning methodologies.