Machine Learning Engineer - Hybrid NYC

Job Summary TECHNICAL SKILLS Must Have Applied Machine Learning Azure Databricks Big Data Analytics Databricks Certified Data Engineer Associate Data Structures google cloud certified machine learning engineer Machine Learning Operations Pandas Python Library PySpark Job Description Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field. Strong experience in machine learning algorithms, predictive modeling, and data mining. Proficiency in Pyspark, Python pandas (required) for data science workloads. Strong SQL (required) Knowledge And Experience With Relational Databases. Minimum 3 years of experience with data visualization tools such as Power BI, Dax Queries, and best practices. Experience with Azure Databricks, Google Cloud, and modern data science libraries (e.g., scikit-learn, pandas, NumPy). Experience with GenAI and large language models. Ability to interpret complex datasets and produce actionable insights. Must know how to analyze the root cause of dashboard errors. Have experience in ML Ops and have strong coding background. Have experience with Natural Language Processing (NLP). Knowledge or experience with A/B Testing. Working knowledge of designing, training, and implementing machine learning models. Familiarity with cloud-based infrastructure Excellent communication and problem-solving skills. 7 or more years of experience in data science and machine learning engineering. Additional Skills (Skills that are a plus, but not required) Knowledge of statistical methods and experimental design. Responsibilities Key Responsibilities Advanced Analytics & Machine Learning Design, develop, and optimize machine learning models (forecasting, classification, clustering). Apply data mining techniques to uncover patterns and insights in large datasets. Perform feature engineering, model validation, and performance tuning. Explore and deploy modern AI and ML approaches to enhance automation and analytics. Data Preparation & Quality Prepare structured and unstructured data for modeling and advanced analysis. Develop scripts and tools for data cleansing, validation, and enrichment. Collaborate with Data Engineering to maintain efficient data pipelines. Identify data quality issues and propose remediation. Analytics, Insights & Reporting Conduct deep-dive analyses to identify trends and improvement opportunities. Communicate complex findings in clear, concise ways to technical and non-technical stakeholders. Support the development of dashboards, metrics, and analytical solutions. Cross-Team Collaboration Work with architects, engineers, and analysts to define analytical requirements. Contribute to conceptual data model design and workflow optimization. Promote best practices in machine learning, analytics, and data governance. location: New York, New York job type: Contract salary: $60 - 65 per hour work hours: 9am to 5pm education: Bachelors Responsibilities JOB DESCRIPTION • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field. • Strong experience in machine learning algorithms, predictive modeling, and data mining. • Proficiency in Pyspark, Python pandas (required) for data science workloads. • Strong SQL (required) knowledge and experience with relational databases. • Minimum 3 years of experience with data visualization tools such as Power BI, Dax Queries, and best practices. • Experience with Azure Databricks, Google Cloud, and modern data science libraries (e.g., scikit-learn, pandas, NumPy). • Experience with GenAI and large language models. • Ability to interpret complex datasets and produce actionable insights. • Must know how to analyze the root cause of dashboard errors. • Have experience in ML Ops and have strong coding background. • Have experience with Natural Language Processing (NLP). • Knowledge or experience with A/B Testing. • Working knowledge of designing, training, and implementing machine learning models. • Familiarity with cloud-based infrastructure • Excellent communication and problem-solving skills. • 7 or more years of experience in data science and machine learning engineering. Additional Skills (Skills that are a plus, but not required) • Knowledge of statistical methods and experimental design. Responsibilities • Key Responsibilities • Advanced Analytics & Machine Learning • Design, develop, and optimize machine learning models (forecasting, classification, clustering). • Apply data mining techniques to uncover patterns and insights in large datasets. • Perform feature engineering, model validation, and performance tuning. • Explore and deploy modern AI and ML approaches to enhance automation and analytics. • Data Preparation & Quality • Prepare structured and unstructured data for modeling and advanced analysis. • Develop scripts and tools for data cleansing, validation, and enrichment. • Collaborate with Data Engineering to maintain efficient data pipelines. • Identify data quality issues and propose remediation. • Analytics, Insights & Reporting • Conduct deep-dive analyses to identify trends and improvement opportunities. • Communicate complex findings in clear, concise ways to technical and non-technical stakeholders. • Support the development of dashboards, metrics, and analytical solutions. • Cross-Team Collaboration • Work with architects, engineers, and analysts to define analytical requirements. • Contribute to conceptual data model design and workflow optimization. • Promote best practices in machine learning, analytics, and data governance. Qualifications MUST have MLops, PysSpark, SQL, AI experience Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status. At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com. Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility). This posting is open for thirty (30) days.