Data Scientists - Enterprise AI, ML & Advanced Analytics

Were Hiring: Data Scientists Enterprise AI, ML & Advanced Analytics

(30+ Openings | 3-20 Yrs Exp | Multiple Levels)

Location:

About us:

Hatchtra is a leading staffing and workforce solutions company, trusted by Fortune 500 organizations and global enterprises to build their technology teams.

When you join us, you'll work directly with our Fortune 500 client teams that power mission-critical systems worldwide.

About the Role

Data Scientists (3-20 years)

enterprise AI initiatives, ML model deployment, NLP, computer vision, and generative AI

Open Positions & Designations

• Associate Data Scientist / Junior ML Engineer

  (3–5 Yrs)

• Data Scientist / Senior Data Scientist

  (5–10 Yrs)

• Lead Data Scientist / AI Engineer

  (8–12 Yrs)

• Principal Data Scientist / AI Solutions Architect

  (10–15 Yrs)

• Director – Data Science & AI Strategy

  (15–20 Yrs)

Key Responsibilities (Scale with Level)

Professional (3–5 Yrs)

• Clean, preprocess, and analyze structured and unstructured data for model building.
• Build and evaluate

  ML models

  (classification, regression, clustering).
• Work with Python, R, and libraries like

  Scikit-learn, TensorFlow, PyTorch

  .
• Support data preparation, feature engineering, and exploratory data analysis (EDA).
• Create basic dashboards and visualizations to share findings with stakeholders.
• Collaborate with data engineers to productionize analytics pipelines.

Mid-Level (5–10 Yrs)

• Design and deploy

  end-to-end ML/AI solutions

  in enterprise environments.
• Develop

  deep learning models

  for NLP, computer vision, and recommendation systems.
• Integrate ML pipelines with

  cloud data platforms

  (AWS SageMaker, Azure ML, GCP Vertex AI).
• Implement

  MLOps best practices

  for model lifecycle management.
• Conduct advanced statistical modeling, A/B testing, and causal inference.
• Mentor junior team members and lead analytics initiatives.

Senior/Leadership (10–20 Yrs)

• Define and execute

  enterprise AI and data science strategy

  .
• Lead

  AI innovation programs

  (Generative AI, LLMs, reinforcement learning).
• Partner with executives to drive

  AI-driven digital transformation initiatives

  .
• Build and manage

  global data science teams

  and delivery frameworks.
• Ensure AI/ML governance, ethical AI compliance, and data privacy standards.
• Represent organization in

  AI/ML conferences, publications, and thought leadership

  .

Skills & Tools

• Core Skills:

  Machine Learning, Deep Learning, NLP, Predictive Modeling, AI Solutions

• Programming:

  Python, R, SQL, Java, Scala

• ML Frameworks:

  TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face Transformers

• Cloud AI Platforms:

  AWS SageMaker, Azure ML, GCP Vertex AI

• Big Data:

  Spark, Databricks, Snowflake, BigQuery, Redshift

• Visualization:

  Power BI, Tableau, Matplotlib, Seaborn

• MLOps Tools:

  MLflow, Kubeflow, Airflow, Docker, Kubernetes

• Preferred Certifications:

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

Qualifications

• Bachelor’s/Master’s/PhD in Data Science, Computer Science, Statistics, Mathematics, or related field.

• 3+ years of experience

  in data science, AI, or advanced analytics roles.
• Proven expertise in building

  ML/DL models

  and deploying them in production.
• Experience with

  big data ecosystems and cloud AI platforms

  .
• For leadership roles: Strong experience in strategy, innovation, and global team management.

Why Join Us?

• Collaborate with

  Fortune 500 enterprises

  on

  AI-first transformation projects

  .
• Work on cutting-edge

  ML, deep learning, NLP, and generative AI initiatives

  .
• Exposure to

  global projects, certifications, and leadership opportunities

  .
• Competitive compensation, remote flexibility, and global career growth.

How to Apply

For quick consideration, please email your resume and include the desired position and experience level (e.g., “Data Engineer – Mid-Level”) in the subject line.