Danta Technologies
Lead Data Scientist Retail Analytics
Danta Technologies, San Francisco, California, United States, 94199
Lead Data Scientist Retail Analytics
Danta Technologies is hiring a Lead Data Scientist Retail Analytics. This position is located in San Francisco, California, and requires on?site presence. Only independent candidates with valid work authorization are eligible for this position. Location
San Francisco, California - Onsite Duration
Contract + months with possibility for extension; duration may change based on project requirements and client discretion. Client Industry
Retail Pay Rate
$ / hr - $ / hr on W All Inclusive Danta Technologies payroll Ideal Candidate
A senior?level, hands?on data science professional with retail?specific analytics expertise, leadership experience, strong Python + SQL + DevOps + ADF skills, and the ability to build and deploy ML models in cloud environments. Top Focus Areas Business?impactful analytics in retail Technical depth (ML, pipelines, visualization) Leadership and stakeholder management
What the Client is Exactly Looking For
Leadership in Data Science & Analytics lead and mentor a team of data scientists and analysts, own end?to?end analytics and ML project delivery, be the go?to expert in analytics for retail domain use cases. Domain Expertise: Retail strong understanding of merchandising, pricing, supply chain, customer behavior, omnichannel analytics; proven experience applying analytics to forecasting, pricing & promotions, segmentation & churn prediction, inventory optimization. Hands?on Technical Skills required: Azure Data Factory, SQL (DataOps practices), Python, DevOps (especially for data or ML pipelines); preferred: Spark, R, Databricks; data visualization: Power BI, Tableau, Looker; cloud platforms: Azure, AWS, GCP; MLOps practices (CI/CD for ML models, model monitoring). Business Acumen & Stakeholder Influence translate business needs into data products, communicate insights and model outputs in business terms, drive data adoption and strategic decision?making. Project & People Management experience in Agile / SAFe environments, lead cross?functional collaboration with data engineering, product, and business teams, deliver results in production environments.
Job Summary
We are looking for an experienced Data Science & Analytics Lead to drive data?driven decision?making and advanced analytics initiatives in the retail domain. This onsite role will work closely with business stakeholders, product teams, and data engineering to deliver actionable insights, predictive models, and AI/ML?powered solutions aligned with retail business goals. Key Responsibilities
Lead data science and analytics initiatives across core retail functions (merchandising, pricing, supply chain, customer behavior, marketing, omnichannel operations). Collaborate with business leaders to define analytics use cases and translate them into high?impact solutions. Build, deploy, and manage machine learning models and statistical algorithms for forecasting, segmentation, recommendations, and optimization. Interpret and present analytical findings in business?friendly terms, driving adoption of insights and models. Work closely with data engineering teams to ensure data availability, quality, and proper pipeline design. Lead and mentor junior data scientists and analysts, fostering a culture of experimentation and innovation. Drive adoption of analytics tools and platforms across the organization dashboards, self?service BI, ML platforms.
Primary Skills
Strong expertise in data science, machine learning, and statistical modeling. Proficiency in tools and languages such as Python, R, SQL, Spark, and Databricks. Experience with retail analytics use cases such as sales & demand forecasting, price & promotion analytics, customer segmentation & churn prediction, inventory & supply chain optimization, assortment & space planning. Hands?on experience with data visualization tools like Power BI, Tableau, or Looker. Familiarity with cloud ecosystems (Azure, AWS, or GCP) and MLOps practices is a plus. Strong business acumen and ability to influence stakeholders with data.
Qualifications
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field. Years of experience in analytics or data science, preferably in the retail domain. Proven track record in leading data science projects from ideation to production. Experience working in Agile / SAFe environments and collaborating with cross?functional teams. Certifications in data science, cloud platforms, or analytics tools are a plus.
Notes
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance. Benefits
Compensation package includes competitive pay, healthcare insurance options (Dental, Medical, Vision), major holidays, and paid sick leave as per state law. Salary ranges depend on qualification, experience, and location. #J-18808-Ljbffr
Danta Technologies is hiring a Lead Data Scientist Retail Analytics. This position is located in San Francisco, California, and requires on?site presence. Only independent candidates with valid work authorization are eligible for this position. Location
San Francisco, California - Onsite Duration
Contract + months with possibility for extension; duration may change based on project requirements and client discretion. Client Industry
Retail Pay Rate
$ / hr - $ / hr on W All Inclusive Danta Technologies payroll Ideal Candidate
A senior?level, hands?on data science professional with retail?specific analytics expertise, leadership experience, strong Python + SQL + DevOps + ADF skills, and the ability to build and deploy ML models in cloud environments. Top Focus Areas Business?impactful analytics in retail Technical depth (ML, pipelines, visualization) Leadership and stakeholder management
What the Client is Exactly Looking For
Leadership in Data Science & Analytics lead and mentor a team of data scientists and analysts, own end?to?end analytics and ML project delivery, be the go?to expert in analytics for retail domain use cases. Domain Expertise: Retail strong understanding of merchandising, pricing, supply chain, customer behavior, omnichannel analytics; proven experience applying analytics to forecasting, pricing & promotions, segmentation & churn prediction, inventory optimization. Hands?on Technical Skills required: Azure Data Factory, SQL (DataOps practices), Python, DevOps (especially for data or ML pipelines); preferred: Spark, R, Databricks; data visualization: Power BI, Tableau, Looker; cloud platforms: Azure, AWS, GCP; MLOps practices (CI/CD for ML models, model monitoring). Business Acumen & Stakeholder Influence translate business needs into data products, communicate insights and model outputs in business terms, drive data adoption and strategic decision?making. Project & People Management experience in Agile / SAFe environments, lead cross?functional collaboration with data engineering, product, and business teams, deliver results in production environments.
Job Summary
We are looking for an experienced Data Science & Analytics Lead to drive data?driven decision?making and advanced analytics initiatives in the retail domain. This onsite role will work closely with business stakeholders, product teams, and data engineering to deliver actionable insights, predictive models, and AI/ML?powered solutions aligned with retail business goals. Key Responsibilities
Lead data science and analytics initiatives across core retail functions (merchandising, pricing, supply chain, customer behavior, marketing, omnichannel operations). Collaborate with business leaders to define analytics use cases and translate them into high?impact solutions. Build, deploy, and manage machine learning models and statistical algorithms for forecasting, segmentation, recommendations, and optimization. Interpret and present analytical findings in business?friendly terms, driving adoption of insights and models. Work closely with data engineering teams to ensure data availability, quality, and proper pipeline design. Lead and mentor junior data scientists and analysts, fostering a culture of experimentation and innovation. Drive adoption of analytics tools and platforms across the organization dashboards, self?service BI, ML platforms.
Primary Skills
Strong expertise in data science, machine learning, and statistical modeling. Proficiency in tools and languages such as Python, R, SQL, Spark, and Databricks. Experience with retail analytics use cases such as sales & demand forecasting, price & promotion analytics, customer segmentation & churn prediction, inventory & supply chain optimization, assortment & space planning. Hands?on experience with data visualization tools like Power BI, Tableau, or Looker. Familiarity with cloud ecosystems (Azure, AWS, or GCP) and MLOps practices is a plus. Strong business acumen and ability to influence stakeholders with data.
Qualifications
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field. Years of experience in analytics or data science, preferably in the retail domain. Proven track record in leading data science projects from ideation to production. Experience working in Agile / SAFe environments and collaborating with cross?functional teams. Certifications in data science, cloud platforms, or analytics tools are a plus.
Notes
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance. Benefits
Compensation package includes competitive pay, healthcare insurance options (Dental, Medical, Vision), major holidays, and paid sick leave as per state law. Salary ranges depend on qualification, experience, and location. #J-18808-Ljbffr