AI/ML Data Scientist - Sales Forecasting

Posted Yesterday
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Bangalore, Bengaluru Urban, Karnataka, IND
In-Office
Mid level
Healthtech • Telehealth
The Role
Design, build, and deploy scalable time-series and ML demand-forecasting models; develop discount and price-simulation tools; own full ML lifecycle including data engineering, feature engineering, deployment, monitoring, and iteration; maintain data pipelines and ensure data quality; present insights to stakeholders and collaborate cross-functionally to operationalize models.
Summary Generated by Built In
Job TitleAI/ML Data Scientist - Sales Forecasting

Job Description

Job Responsibilities:

  • Demand Forecasting: Design, build, and deploy scalable demand forecasting models (time-series, ML-based) to predict product demand at SKU, category, channel, and regional levels.
  • Discount & Price Simulation: what-if simulation tools to optimize discount strategies and maximize margin.
  • End-to-End Model Ownership: Own the full ML lifecycle—data exploration, feature engineering, model training, validation, deployment, monitoring, and iteration.

•Analyzes multifaceted and high-dimensional data problems, developing innovative solutions, formulating sophisticated hypotheses, and creating advanced proof of concepts to validate and refine analytical models.
• Ensures the highest standards of data quality, accuracy, and reliability by designing and implementing rigorous validation protocols, advanced data cleansing techniques, and comprehensive quality control measures, working under limited supervision.
• Participates in end-to-end data mining projects, utilizing advanced algorithms, machine learning models, and AI techniques to extract deep and actionable insights from complex, large-scale data sources.
• Executes the deployment and rigorous testing of data science solutions and insights, ensuring optimal performance, scalability, and seamless integration with existing enterprise systems and workflows.
• Maintains robust, scalable data pipelines and workflows, leveraging cutting-edge big data technologies and database management systems to support advanced analytics and machine learning projects.
• Develops, documents, and disseminates comprehensive methodologies, processes, and analytical findings, ensuring transparency, reproducibility, and facilitating cross-functional knowledge sharing and collaboration.
• Evaluates and implements state-of-the-art machine learning and AI techniques, continuously researching and applying novel approaches to solve highly complex business problems and drive strategic innovation within Philips.
• Presents complex data-driven insights and strategic recommendations to senior stakeholders, effectively translating intricate analytical results into clear, actionable business strategies and influencing key decision-making processes.
• Monitors, maintains, and continuously improves the performance of deployed models, conducting regular reviews, updates, and optimizations to ensure sustained accuracy, relevance, and business impact.
• Interacts and collaborates with cross-functional teams, including IT, data engineering, and various business units, to ensure the successful operationalization, integration, and scaling of data science solutions across the organization.
Minimum required Education:
Bachelor's / Master's Degree in Computer Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or equivalent.
Minimum required Experience:
Minimum 3 years of experience with Bachelor's in areas such as Data Analytics, Data Science, Data Mining, Artificial Intelligence, Pattern Recognition or equivalent OR no prior experience required with Master's Degree.
Preferred Skills:
• Data Analysis & Interpretation
• Data Governance
• Statistical Methods
• Statistical Programming Software
• Business Intelligence Tools
• Data Mining
• Machine Learning Engineering Fundamentals
• Research & Analysis
• Requirements Analysis
• Root Cause Analysis (RCA)
• Data Quality Management Systems
• Regulatory Compliance

How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.
Onsite roles require full-time presence in the company’s facilities.
Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.
Indicate if this role is an office/field/onsite role.

About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.
• Learn more about our business.
• Discover our rich and exciting history.
• Learn more about our purpose.
If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here.

Skills Required

  • Bachelor's or Master's Degree in Computer Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or equivalent
  • Minimum 3 years of relevant experience (with Bachelor's) OR Master's degree (no prior experience required)
  • Design, build, and deploy scalable demand-forecasting models (time-series, ML-based)
  • End-to-end ML lifecycle ownership: data exploration, feature engineering, model training, validation, deployment, monitoring, and iteration
  • Develop discount and price what-if simulation tools to optimize pricing strategies and margins
  • Maintain robust, scalable data pipelines and workflows using big data technologies and database management systems
  • Data Analysis & Interpretation
  • Data Governance
  • Statistical Methods
  • Statistical Programming Software
  • Business Intelligence Tools
  • Data Mining
  • Machine Learning Engineering Fundamentals
  • Research & Analysis
  • Requirements Analysis
  • Root Cause Analysis (RCA)
  • Data Quality Management Systems
  • Regulatory Compliance

Philips Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Philips and has not been reviewed or approved by Philips.

  • Retirement Support Retirement support is positioned as a standout, including a strong 401(k) match (often described at 7%) alongside pensions in some contexts.
  • Flexible Benefits Flexible benefits are emphasized through choice in health insurance options and a broad “Total Rewards” approach that combines compensation, health and wellness, and work-life support.
  • Leave & Time Off Breadth Leave and time off breadth appears strong, with generous paid time off and policies covering parental leave, caregiving responsibilities, volunteering, and family medical leave.

Philips Insights

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The Company
HQ: Cambridge, MA
80,000 Employees
Year Founded: 1891

What We Do

Do the work of your life to help the lives of others. As a leading health technology company, it is our purpose to improve people’s health and well-being through meaningful innovation. Our goal is to improve 2.5 billion lives per year by 2030. ​ ​ We also strive to be the best place to work for people who share our passion, by promoting personal development, inclusion and diversity while acting responsibly towards our planet and society.

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