Hybrid Data Scientist /ML Engineer

New York, NY, US • Posted 24 days ago • Updated 1 day ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Recruiting
  • Forecasting
  • Clustering
  • Performance Tuning
  • Unstructured Data
  • Advanced Analytics
  • Use Cases
  • Data Cleansing
  • Collaboration
  • Data Engineering
  • Dashboard
  • Root Cause Analysis
  • Visualization
  • Data Governance
  • Computer Science
  • Statistics
  • Mathematics
  • Algorithms
  • Predictive Modelling
  • Data Mining
  • Python
  • SQL
  • Relational Databases
  • PySpark
  • Data Processing
  • Microsoft Azure
  • Databricks
  • Generative Artificial Intelligence (AI)
  • Large Language Models (LLMs)
  • Natural Language Processing
  • Machine Learning Operations (ML Ops)
  • Lifecycle Management
  • Microsoft Power BI
  • DAX
  • Data Visualization
  • Data Science
  • scikit-learn
  • Pandas
  • NumPy
  • A/B Testing
  • Statistical Models
  • Design Of Experiments
  • Communication
  • Analytical Skill
  • Conflict Resolution
  • Problem Solving
  • Google Cloud Platform
  • Google Cloud
  • Cloud Computing
  • Oracle
  • Database
  • Analytics
  • Machine Learning (ML)

Summary

Crossfire is a temporary hiring firm - this role is a contract position with our client:

Position: Data Scientist/ML Engineer
Contract Length: 12 months
Location: New York, NY
Work Setup: Hybrid

Our client is a data-driven organization leveraging advanced analytics, machine learning, and cloud technologies to deliver impactful business insights. The Data Scientist/ML Engineer will design, build, and deploy scalable machine learning solutions while collaborating with cross-functional teams in a modern enterprise environment.
Data Scientist/ML Engineer Responsibilities
  • Design, develop, and optimize machine learning models for forecasting, classification, and clustering.
  • Apply advanced analytics, data mining, and statistical techniques to uncover trends and predictive insights.
  • Perform feature engineering, model validation, performance tuning, and deployment using MLOps best practices.
  • Prepare and analyze structured and unstructured data for advanced analytics and machine learning use cases.
  • Develop and maintain Python and PySpark code for data cleansing, enrichment, and validation.
  • Collaborate closely with Data Engineering teams to support and optimize scalable data pipelines.
  • Build, maintain, and troubleshoot Power BI dashboards, including root-cause analysis of data and visualization issues.
  • Conduct deep-dive analyses and clearly communicate findings to technical and non-technical stakeholders.
  • Partner with architects, engineers, and analysts to define analytical requirements and promote data governance standards.
Data Scientist /ML Engineer Qualifications

Required (Must Have):
  • Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related field.
  • 7+ years of experience in data science and machine learning engineering roles.
  • Strong hands-on experience with machine learning algorithms, predictive modeling, and data mining.
  • Advanced proficiency in Python (required), including full-stack Python development.
  • Advanced SQL (required) with strong experience in relational databases.
  • Proficiency in PySpark (required) for large-scale data processing and analytics.
  • Azure Databricks Data Engineer Associate certification (REQUIRED).
  • Hands-on experience using Azure Databricks in enterprise data and ML environments.
  • Experience with Generative AI, large language models, and Natural Language Processing (NLP).
  • Strong experience with Machine Learning Operations (MLOps), including model deployment, monitoring, and lifecycle management.
  • Minimum 3 years of experience with Power BI, DAX queries, and data visualization best practices.
  • Experience with modern data science libraries such as scikit-learn, pandas, and NumPy.
  • Knowledge of A/B testing, statistical modeling, and experimental design.
  • Ability to interpret complex datasets and translate insights into actionable business recommendations.
  • Excellent communication, analytical, and problem-solving skills.

Nice to Have:
  • Experience with Google Cloud Platform (Google Cloud Platform), including BigQuery.
  • Exposure to multi-cloud or hybrid cloud data environments.
  • Experience with Oracle or other enterprise database platforms.

This Data Scientist /ML Engineer role offers the opportunity to work on high-impact analytics and machine learning initiatives in a collaborative, hybrid environment based in New York, NY.
We look forward to reviewing your application!
#tech
#NoLinkedIn
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10117531
  • Position Id: 26-00144
  • Posted 24 days ago
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