Senior Data Scientist
Senior Data Scientist
Grid Dynamics5-10 Years
- Posted 6 hours ago
- Be among the first 10 applicants
Job Description
We are seeking a skilled Demand Forecasting & Time Series Analysis Engineer to develop, deploy, and optimize forecasting models that improve business planning.
Responsibilities
5–10 years of overall experience, who can independently drive modelling and implementation with minimal supervision.
Experience In Time Series Forecasting
Demand Forecasting
Python / Pyspark
Machine Learning
CICD
Databricks
ADF pipelines / Azure
Nice to have
MLOps
We offer
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.
Responsibilities
- Design, develop, and maintain demand forecasting models
- Develop automated forecasting pipelines for production deployment.
- Collaborate with business teams to understand forecasting requirements.
- Monitor forecast performance and continuously improve model accuracy.
- Build dashboards and reports to communicate forecasting insights.
5–10 years of overall experience, who can independently drive modelling and implementation with minimal supervision.
Experience In Time Series Forecasting
Demand Forecasting
Python / Pyspark
Machine Learning
CICD
Databricks
ADF pipelines / Azure
Nice to have
MLOps
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.
More Info
Key Skills
Time Series Forecasting
ADF pipelines
About Company
Skills:
Machine Learning, Deep Learning, Data Science, Python, Generative AI, explainable AI, Forecasting, ML libraries, model evaluation, Statistical Modeling, time-series analysis, cloud-based ML platforms
Skills:
Statistical Analysis, Nlp, Machine Learning, Gitlab, Jira, Python, Sql, UNIX command line, Azure AI Search, Feature engineering
Skills:
data quality control , data engineering , Databricks, Python, Sql, MLops, MLflow, Data pipeline automation, Model deployment, Reproducibility practices, Model inference, Inference pipelines, Model training
Skills:
snowflake , Machine Learning, Tensorflow, Nlp, Pytorch, Docker, Azure DevOps, Sql, Deep Learning, Keras, Kubernetes, MLflow, LangGraph, Vector Databases, GitHub Actions, Azure AI ecosystem, Azure AI Search, RAG architectures, LangChain, Generative AI, Semantic Kernel, Agentic AI, Statistical Modeling, Embedding Models
Skills:
Predictive Analytics, Power Bi, Hypothesis Testing, Version Control, ADO, Code Management, Sql, Recommender Systems, Git, Google Analytics, Python, Machine Learning Algorithms, cloud platforms, ML Ops practices, R, Statistical Modeling, Experimental Design, Forecasting Models