Data Science Manager - Data Analytics
Purpose & Overall Relevance For The Organization
Driving Data science solutions across Planning, Consumer Engagement, Pricing, Merchandising, Operations verticals at adidas e-commerce, you are responsible delivering cutting-edge data driven data science services to stakeholders, enabling them to make decisions generating value to business. Based on internal & external data sources, you manage the creation and generation of ML and statistical based solutions, forecast models, data capabilities, insights that help adidas better understand the consumer, expand reach, increase customer engagement and advocacy, and ultimately drive sales. In collaboration with business team, you drive and execute EM Digital Data Science strategy focussing on Emerging markets, supporting planning teams in key KPIs relevant to drive net sales for E-commerce business
Key Responsibilities
Data Science
:
- Develop and deliver forecasting & pricing models for KPIs critical to business planning and financial reporting. Utilize time series-based algorithms (e.g., Prophet, ARIMA, and variants), machine learning algorithms (e.g., XGBoost, LightGBM), and deep learning algorithms (e.g., LSTM, GRU, DeepAR, TCN, Chronos, TFT)
- Hands-on experience with forecasting libraries (e.g., NeuralProphet, GluonTS, Darts, Nixtla, Sktime, or StatsForecast).
- Develop and validate causal inference models to estimate treatment effects using observational data.
- Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, DevOps function
- Should be curious to learn & experiment latest developments in Data Science and AI reasearch
- Design and build MMM models to quantify the ROI of marketing channels
- Operationalize existing data science models with knowledge of model deployment on cloud based platforms like Databricks, AWS, Azure
- Apply expertise in various AI/ML techniques including deep learning, NLP, recommender systems, reinforecement learning and LLMs
- Scale existing models to different geographies, ensuring they are adaptable and effective across diverse regions
- Conduct data feasibility analysis, including data preparation and cleaning to ensure high-quality inputs for modeling
- Observe trends from data and leverage these trends to support feature engineering and enhance model performance
- Work closely with local and global teams in Planning, Marketing, Operations, and Data Engineering to ensure seamless integration of data science solutions
- Clearly translate complex business problems into data science and analytics solutions, incorporating feedback from business stakeholders
- Maintain quality, set good development practices, and define standards that keep the focus on the right things
- Support deep-dives, ad-hoc analysis and contextual dashboards with relevant platforms and channels
- Develop and maintain a strong stakeholder network with high level of trust that facilitates action- ability of insights
- Collaborate with the internal analytics team in your area of responsibility on digital analytics to define goals, select appropriate KPIs, monitor performance and derive trends and opportunities
- Excellent deck creation skills augemnted with story telling and ability to communicate complex data science topics with simplicity
- Participate in code reviews, brainstorming new use cases, mentor j& unior data scientists in the team
Key Relationships
- EM Hub & cluster e-com team
- EM Function teams (Finance, DNA, Brand, Sales, SCM…)
- Global Digital teams
- Global BI & Analytics teams
- Global Digital Data Science teams
- External vendors
Requisite Education And Experience / Minimum Qualifications
- Bachelor’s or Masters degree in computer science, Information Technology, Mathematics, computing, Software Engineering, or a related field from a Tier-1 college
- Alternatively, an MBA with a focus on Analytics or Data Science specialization is preferred
- 6+ years of experience working in Digital Data Science , Digital Analytics, Business Intelligence, Demand forecasting & planning, Market mix modeling, Causal Inference, Pricing analytics, customer lifetime value modeling, SKU level forecasting
Hard Skills
- Well versed with classification, clustering, multiclassification, segmentation techniques
- Proven experience with time series algorithms (e.g., Prophet, ARIMA) & Causal Inference
- Proficiency in machine learning algorithms (e.g., Xgboost, LightGBM) and deep learning algorithms (e.g., LSTM, GRU, DeepAR, TCN).
- Should have knowledge on LLMs, Agentic AI with atleast one POC/project developed using these technologies
- Experience with Databricks & AWS services (e.g., S3, EMR, SageMaker, AWS Lambda) is preferred
- Familiarity with UI tools such as Streamlit, Flask, FAST APIs, Rest APIs, Docker containers
- Hands-on experience with SQL, Python, Power BI, PySpark, Excel and building data pipelines, writing production ready code.
- Prior experience in Consumer, pricing, risk, recommendation, ranking domain within Ecommerce/Retail/Banking preferred
- Prior experience with model deplyoyment, CI/CD pipelines development
- Prior experience with Fine tuning LLMs, validating LLM outputs is good to have
- Knowledge of tools like Adobe Analytics, google Analytics, Kibana, JIRA, Appsflyer, Amplitude, Jenkins, Bitbucket, Git is good to have
- Industry: Ideally in apparel/fashion/shoes or internet/retail banking
- Experience in e-commerce environment
Knowledge & Soft Skills
- Ability to efficiently work in a cross-functional organization, ability to develop influential and collaborative relationships with stakeholders from digital and non-digital disciplines on all levels
- Excellent communication skills, comfortable presenting complex topics to technical and non-technical audience both in person and remotely at various organizational levels
- A passion for designing and creating new data capabilities, tools, and frameworks. Interest in “back-of-house” development of analytics capabilities. Devotion to accuracy, reliability, rigor, and user-focused design.
- Meticulous, high attention to details
- Creative and energetic team player who has a passion for delivering analytics, data, insights to drive outcomes for quantifiable improvements in business results and consumer satisfaction.
- Outspoken and Confident
- Broad understanding of and passion for the sports and fashion/entertainment industry
- Project management skills, including the ability to lead projects or work on several projects simultaneously.
- Fluent English both verbally and written
- Proficient in documenting technical details of solutions, creating requirement documents, powerpoint presentations
adidas celebrates diversity, supports inclusiveness and encourages individual expression in our workplace. We do not tolerate the harassment or discrimination toward any of our applicants or employees. We are an equal opportunity employer.
