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Data Scientist - Raleigh, NC, Dallas, TX, Richmond, VA, Alpharetta, GA, Santa Fe, NM.

100% remote Flexible hours Hiring now

Dice is the leading career destination for tech experts at every stage of their careers. Our client, TechniPros, LLC, is seeking the following. Apply via Dice today! Job Title: Data Scientist Location: Raleigh, NC, Dallas, TX, Richmond, VA, Alpharetta, GA,Santa Fe, NM. Long Term Contact Can do Only W2, No C2C Job Summary: We are seeking a highly motivated Data Scientist to join our team in Dallas, TX. The ideal candidate will be responsible for transforming raw data into actionable business insights, developing predictive models, and supporting data-driven decision-making processes. This role requires expertise in machine learning, statistical analysis, data modeling, and modern AI/ML technologies. Key Responsibilities:

  • Extract actionable insights from large and complex datasets to support strategic business decisions.
  • Design, develop, and deploy predictive models and machine learning algorithms to forecast trends and outcomes.
  • Analyze data to identify patterns, anomalies, risks, and opportunities for process improvement.
  • Build data-driven solutions that enable business stakeholders to make informed decisions.
  • Develop analytical reports, dashboards, and visualizations to communicate findings effectively.
  • Collaborate with cross-functional teams including business stakeholders, engineers, and product teams.
  • Utilize modern AI/ML frameworks and cloud technologies to build scalable data science solutions.
  • Support model monitoring, validation, and optimization activities.
  • Required Skills
  • experience as a Data Scientist, Data Analyst, Machine Learning Engineer, or related role.

Strong understanding of:

  • Statistics
  • Probability
  • Data Modeling
  • Proficiency in:
  • Python
  • R
  • SQL
  • Experience with Machine Learning frameworks and libraries:
  • Scikit-learn
  • TensorFlow
  • PyTorch
  • Hands-on experience with Generative AI and LLM technologies:
  • LangChain
  • OpenAI APIs
  • Hugging Face

Experience with MLOps tools:

  • MLflow
  • Docker
  • Apache Airflow
  • Experience working with AWS Cloud Services.
  • Preferred Qualifications
  • Experience building and deploying production-grade machine learning solutions.
  • Knowledge of end-to-end ML lifecycle management and model deployment practices.
  • Exposure to Generative AI, Large Language Models (LLMs), and AI application development.
  • Familiarity with cloud-native AI/ML architectures on AWS.
  • Experience with data visualization and reporting tools.

Best Regards: Bindu M Phone: Email: Apply To This Job

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