Data Scientist - AI/ML

Role: Sr. Data Scientist – AI/ML

Type: Contract

Duration: 6–9 months

Location: Chantilly, VA (3 days onsite required)

Job Description

We are seeking a highly experienced Senior Data Scientist with strong expertise in AI/ML to lead the development of advanced analytics and machine learning solutions. The ideal candidate will drive end-to-end model development, guide data science best practices, and work closely with business, data engineering, and product teams to deliver scalable, production-ready AI solutions.

Key Responsibilities

• Lead analysis of large, complex datasets to identify trends, risks, and business opportunities.
• Design, build, validate, and deploy advanced machine learning and AI models.
• Develop models for classification, regression, clustering, NLP, and time-series forecasting.
• Perform advanced feature engineering, data preprocessing, and EDA.
• Design and evaluate A/B tests and statistical experiments to measure business impact.
• Partner with data engineers to design scalable data pipelines and ML workflows.
• Guide model deployment, monitoring, drift detection, and retraining strategies.
• Apply explainable AI (XAI) techniques to ensure model transparency and compliance.
• Present insights and recommendations to senior stakeholders and business leaders.
• Mentor junior data scientists and establish data science best practices.
• Ensure data quality, governance, privacy, and regulatory compliance.

Required Skills

• 12+ years of experience in data science, analytics, or applied machine learning.
• Expert-level programming in Python (preferred) or R.
• Strong experience with SQL and relational/analytical databases.
• Deep knowledge of machine learning algorithms and model evaluation techniques.
• Hands-on experience with TensorFlow, PyTorch, scikit-learn, pandas, and NumPy.
• Strong foundation in statistics, probability, and experimental design.
• Experience with NLP, deep learning, recommendation systems, or time-series models.
• Knowledge of LLMs, prompt engineering, embeddings, and Gen AI use cases is a strong plus.
• Experience with model optimisation and hyperparameter tuning.
• Experience with cloud platforms: AWS, Azure, or Google Cloud Platform.
• Experience with Spark, Data bricks, or distributed computing frameworks.
• Hands-on with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
• Experience implementing CI/CD pipelines for ML models.
• Strong experience with Tableau, Power BI, or Python visualisation libraries.
• Ability to translate complex models into business-friendly insights.
• Experience with real-time ML systems and streaming data (Kafka, Flink).
• Experience building end-to-end AI platforms or model marketplaces.
• Prior experience in regulated industries: Finance, Healthcare, Telecom, or Retail.
• Experience with graph analytics or causal inference.