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Harris Allied

Machine Learning Engineer/Time Series Data

Harris Allied, Danbury, Connecticut, us, 06813

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Machine Learning Engineer/Time Series Data

Industry leading tech company has immediate need for a

Machine Learning Engineer

with expertise in

time series data analysis.

This engineer will drive the development and optimization of machine learning solutions, focusing on

time series forecasting, anomaly detection, and predictive analytics.

This person will use advanced machine learning concepts to design and build impactful real-world applications that drive the business and create opportunities for growth. Responsibilities Develop and implement

machine learning models

and algorithms specifically for

time series data analysis. Design and build

scalable data pipelines

to preprocess and transform time series data. Conduct exploratory data analysis to uncover trends, patterns, and insights from time series data. Optimize and fine-tune models for performance, accuracy, and scalability. Experiment with and implement state-of-the-art techniques for

time series forecasting

and anomaly detection. Develop

RESTful APIs

and interfaces for time series-based services. Analyze complex datasets to create actionable insights, employing advanced machine learning and statistical models. Design end-to-end machine learning pipelines, including data collection, preprocessing, model training, and deployment. Solve business challenges using

predictive analytics, anomaly detection, and recommendation systems. Contribute to research publications, patents, and technical workshops. Partner with cross-functional teams to define and deliver machine learning-based solutions. Ensure machine learning systems meet ethical guidelines, focusing on transparency, fairness, and accountability. Adhere to privacy laws and regulations, implementing measures to safeguard sensitive data. Qualifications 5+ years of hands-on, professional experience with

time series data analysis and deploying machine learning models and pipelines in a production environment. Hands-on development skills with

Python or R

and experience with RESTful API design. Bachelor's or master's degree in Computer Science, Data Science, Statistics, or a related field with specialization in AI, NLP, or Data Science. Proficiency in machine learning development using frameworks such as TensorFlow, PyTorch, or Keras. Experience developing and optimizing machine learning models for

time series forecasting and anomaly detection. Strong data engineering and analytics skills, with tools such as

Pandas, NumPy, Spark, or SQL. Familiarity with big data technologies

(Hadoop, Kafka, or cloud platforms like AWS/GCP/Azure). Bonus points for familiarity with

LLMs, Vector DBs, and RAG. Practical knowledge of statistical methods and techniques for time series analysis. Ability to work in a fast-paced, collaborative team environment and adapt to evolving priorities. Knowledge of

CI/CD

practices (experience developing and setting up a continuous integration/continuous delivery pipeline). Preferred Skills HTML/JS/CSS React Java MySQL or similar relational database (Postgres, SQL Server) Seniority level

Mid-Senior level Employment type

Full-time Job function

Information Technology Industries

Technology, Information and Media

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