Machine Learning Engineer / Data Scientist – Applied ML & Product Analytics

LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities, and support artificial intelligence initiatives., LatentView Analytics enables leading global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimize investment decisions, and turn unstructured data into valuable business assets.

Job Description: Product Data Scientist, Applied ML (Remote)

About the Role:

Do you enjoy solving business problems and uncovering insights from data? Join the Product Data

Science team within Adobe Experience Cloud! We are a high-impact group that applies machine

learning and advanced analytics to help product, marketing, and engineering teams improve how

customers realize value from Adobe’s enterprise products. This role is ideal for someone who’s curious, quantitative, and eager to grow as a data scientist while working on meaningful, high impact business problems.

In This Role, You Will:

• Design, build and productionize machine-learning models that generate insights, segment users, predict outcomes, and drive measurable business impact.
• Analyze product usage and customer datasets to uncover behavioral patterns, feature adoption trends, and growth opportunities.
• Develop and maintain robust data workflows that clean, transform, and validate structured and unstructured data using scalable tools and platforms (such as Databricks, Spark or similar).
• Create reproducible codebases, notebooks, and utilities that improve efficiency, consistency, and collaboration across analytics and ML projects.
• Practice and promote strong data practices, including transparency, version control, reproducibility, and compliance with governance and security requirements.
• Visualize and communicate analytical results clearly, presenting findings and recommendations that enable stakeholders to make data-driven decisions.
• Collaborate cross-functionally with product managers, marketers, engineers, and other data scientists to define data science questions, design solutions, validate outcomes, and translate results into actionable insights.

You Will Thrive in This Role If You Have:

• Proficiency in Python and SQL, with hands-on experience in data manipulation and applied machine learning using libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib/Seaborn.
• Proven ability in designing and implementing scalable data and feature pipelines using distributed frameworks such as Spark or Databricks, ensuring data quality, performance, and reproducibility.
• Strong foundation in statistics and experimental design, including hypothesis testing, regression, and model evaluation.
• Ability to apply software-engineering best practices; modular, well-documented code, version control (Git), reproducible workflows, and testing for model and data quality.
• Strong problem-solving and critical-thinking skills, with the ability to work rigorously through ambiguity and make sound technical decisions.
• Collaborative mindset and effective communication skills, being able to translate complex technical results into clear insights and work closely with cross-functional partners
• 4+ years of relevant experience in data science or related technical roles, preferably within applied machine learning or product data science environments
• Postgraduate degree or equivalent experience in a quantitative field (such as Statistics, Computer Science, Data Science, Engineering, or related field).

You Could Be an Especially Great Fit If You Have:

• Exposure to NLP, LLMs or Generative AI, including embeddings, topic modeling, prompt engineering, or retrieval-augmented generation (RAG).
• Awareness of MLOps and workflow practices that support scalable, reliable analytics and model deployment (model versioning, monitoring, automation)

LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities, and support artificial intelligence initiatives., LatentView Analytics enables leading global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimize investment decisions, and turn unstructured data into valuable business assets.