We are looking for a Principal Data Scientist to work on financial data forecasting for complex retail problems/challenges. Utilize deep learning methods and architectures to build and deploy state-of-the-art forecasting systems. Will also be working on causal inference problems for scenario-based adjustment.
Our team collaborates closely with Finance teams to enhance financial planning and strategic decision-making through cutting-edge data-driven solutions. We specialize in a range of initiatives, including advanced time series forecasting, which provides actionable insights into trends and patterns, and leveraging Generative AI (GenAI) to produce concise, insightful summaries that empower decision-makers. By integrating these innovative approaches, we strive to drive efficiency, accuracy, and impactful outcomes in financial operations.
Key Responsibilities:
Lead high-caliber team to build large-scale time series forecasting systems
Integrate Global forecasting models (e.g., Temporal Fusion Transformers, Nbeats) to enhance forecasting precision and generate synthetic time series data for better model training.
Develop data science systems and tools for retail and e-commerce applications
Leverage LLMS to summarize and build large scale chat applications
Train large scale neural networks and deploy them as a automated batch pipelines using airflow.
Deploy large scale forecasting pipelines modeling thousands of time series using batch pipelines
Establish cross-functional relationships to maintain win-win situation for the corporation
Collaborate with various product stake holders and business owners to formulate and productionize a solution.
We are a company committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration for employment opportunities without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to
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Master's degree or PHD in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in analytics related field.
Have deep understanding on neural networks, attention architecture and other DL and ML concepts. Familiar with statistical models, such as linear models, generalized linear models, experiment design, and testing. Have experience working with optimization problems.
Proven records of solving business problems using deep learning and machine learning methods.
Familiar with some of the DL packages such as Pytorch, Keras, Tensorflow
Strong software development skills in languages such as Python, SQL, R, Scala, Java
Have experience in involving in deployment and production process.
Have experience working with cross-functional teams, such as engineering and product teams.
Experience with Big Data processing and feature engineering using Spark
Experience with training machine learning models through Cloud Services including Google Cloud Platform and Microsoft Azure
Hands on experience of designing and training large DL models on GPU farm
Causal inference expertise and experiences
Knowledge on LLM
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.