Hi, I'm Leila Soltani.
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Self-driven, quick starter, and passionate Data/Product Scientist with a curious mind who enjoys solving complex, real-world problems at the intersection of data, AI, machine learning, and product development.
About
I have over 8 years of experience designing and delivering end-to-end analytics, experimentation, and evaluation solutions for user-facing products. I enjoy working with large and complex datasets, building statistically sound evaluation frameworks, and applying data-driven and AI-assisted approaches to understand user behavior and improve product quality.
- Languages: Python (AI/ML, evaluation & ETL workflows), R, JavaScript, HTML/CSS
- AI / Machine Learning & Evaluation: Applied Machine Learning & AI Systems, LLM Evaluation Frameworks, Experiment Design & A/B Testing, Statistical Validation & Metrics Design
- Data Engineering & Pipelines: ETL / ELT Pipeline Design, Data Quality Checks & Validation, Scalable Analytics & Evaluation Pipelines
- Data Visualization: Tableau, PowerBI, Domo, Looker, Streamlit
- Tools & Platforms: Git, AWS, DataBricks, JIRA, Amplitude, Adobe Analytics
- Databases: MySQL, PostgreSQL, MongoDB
- Others:Data StoryTelling, Cross-functional Collaboration, Analytics & Product Evaluation, Campaign Management through Public Narrative
I am looking for opportunities that combine data science, AI, machine learning, experimentation, and product development, where I can help build and evaluate intelligent systems at scale.
Experience
- Collaborating with cross-functional teams and community stakeholders to frame impactful, data-driven questions, guiding grassroots participants through the full data science life cycle—from problem definition to actionable insights.
- Tools and Skills:Python, Machine Learning,
- Developed detailed solution documents, outlining business requirements and technical specifications for an AI-driven application, ensuring clarity and alignment for development and deployment.
- Collaborated with clients, product managers, and data engineers to gather and translate business needs into actionable analytics requirements, ensuring seamless integration and effective data utilization.
- Tools and Skills: Azure AI search, Python, SQL, People Management
- Partnered with project managers and the marketing team to define project deliverables that directly supported go-to-market (GTM) strategies.
- Worked with a team of volunteers to gather and incorporate feedback into the minimum viable product (MVP).
- Proofread translations from various sources to ensure they met quality standards and maintained consistency with the overall product.
- Tools and Skills: Crowdin, Teamwork
- Provided data-driven insights to the UX/UI team for the alpha version of CheggMate (Multi-Turn Chat System), leading to redefined KPIs that aligned with AI- driven business needs.
- Redefined KPIs for CheggMate (Multi-Turn Chat System) based on data-driven insights, aligning with AI-driven business needs. Developed Interface Requirement Documents (IRDs) and product launch analytics plans.
- Automated reporting pipelines in Tableau, Amplitude, and Excel, streamlining A/B testing and Go-To-Market (GTM) strategy execution.
- Collaborated on A/B test analysis (design, implementation, and results interpretation) for Chegg’s new LLM platform (MTC) as part of a 4-member core team.
- Tools: Python, DataBricks, Amplitude, SQL, Tableau, Confluence, A/B Testing, Data Storytelling
- Conducted a comprehensive analysis of Covid-19's impact on the business, providing actionable insights to the strategy team, which contributed to a significant increase in company market value.
- Partnered with Product Managers to optimize the company’s e-reader app features, using Amplitude dashboards and models using detailed clickstream data to guide enhancements.
- Performed ROI analyses on multiple products (TBS, Q&A), leading to a strategic shift away from TBS investments and changes to the "In-House" answering team operations in India.
- Tools: Python, R, DataBricks, Amplitude, SQL, Tableau, Domo, Confluence, Strategic Thinking
- Utilized machine learning algorithms to create demand forecasting models for textbook editions, leveraging R and Python on the DataBricks platform.
- Led dynamic pricing implementation for a catalog of over 10M SKUs using time series analysis in R, resulting in significant revenue growth.
- Conducted seasonal adoption analyses to identify potential catalog expansion opportunities for the consignment program, partnering with major American college textbook publishers to drive growth.
- Tools: Python, R, DataBricks, SQL, Tableau, Domo
- Implemented and automated custom data pipelines (ETL) to executive dashboards in Tableau/Domo for the textbook business unit, streamlining reporting and insights delivery.
- Developed and automated detailed marketing funnels for each ISBN using Adobe Analytics and Redshift on the DataBricks platform, enabling near real-time insights into user behavior to optimize pricing decisions.
- Tools: Python, R, DataBricks, SQL, Tableau, Domo
Projects
Skills
Languages and Databases
Python
R
MySQL
PostgreSQL
Frameworks and Platforms
Streamlit
Flask
TensorFlow
PyTorch
Other
Git
AWS
Azure
Power BI
Education
San Jose, CA, USA
Degree: Master of Science in Industrial and System Engineering
- Database Systems
- Data Mining
- Information Engineering
- Logistics for Supply Chain
- Design and Analysis of Engineering Experiments
- Advanced Service Systems Engineering and Management
Relevant Courseworks:
Shairf University of Technology
Tehran
Degree: Industrial Engineering - Operations Research
- Operations Research
- Queuing Theory
- Statistics
- Regression
- Design of Experiments
- Simulation Modeling
- System Dynamics
Relevant Courseworks:
Graduate School of Management and Economics, Shairf University of Technology
Tehran
Degree: MBA - General
- Operations Management
- Marketing Strategy
- Information Systems Management
- Foundations in Finance
- E-commerce
- Decision Modeling
- Leadership and Organisational Behaviour
- Project Management
Relevant Courseworks:
