HTC Global Services is looking to hire consultants to build new things, collaborate with experts, and contribute to client success by leveraging the latest emerging technologies.
Requirements
- Data Science, Big Data, Data Architecture, Data Modeling, Data/Analytics dashboards, Data Mining
- Artificial Intelligence & Expert Systems, Forecasting, Reinforcement Learning
- Proven experience developing and deploying machine learning models in a production environment.
- 2+ years of experience in Google cloud platform with solutions designed and implemented at production scale
- 2+ Experience working with Airflow for scheduling and orchestration of data pipelines
- Expertise in SQL for data querying, manipulation, and database interaction.
- Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques.
Responsibilities
- Design, develop, and implement end-to-end AI/ML pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.
- Ingest, transform, and analyze large datasets to support the team in launching data products in the Data Factory on Google CloudPlatform (GCP).
- Act as a full-stack data scientist to develop and deliver advanced analytics models, including classification, anomaly detection, optimization, LLM, and more.
- Write clean, efficient, and well-documented code in Python for data manipulation, feature engineering, and model development.
- Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing actionable business results
- Examine, interpret and report analytical results in both written reports and in oral presentations to varied audiences.
Other
- Acquire deep understanding of the business problems and translate them into appropriate business solutions
- Excellent oral, written, and interpersonal communication skills.
- Inquisitive, proactive, and interested in learning new tools and techniques
- Comfortable working in a fast-paced and innovative environment where problems are not always well-defined
- Master's degree (M.S.) in Data Science, Computer Science, Business Analytics, Machine Learning, Statistics, or a related quantitative field.
