Senior Predictive Analytics

4 weeks ago

Chennai, India Blackstraw Technologies Full time

Key Responsibilities:

  • Develop and implement predictive models using advanced statistical techniques and machine learning algorithms.
  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and opportunities for optimization.
  • Build, test, and validate statistical models (regression, time-series forecasting, classification, clustering, etc.) to drive decision-making.
  • Collaborate with AI engineers, data scientists, and business stakeholders to translate business challenges into data-driven solutions.
  • Deploy models into production environments and monitor their performance, accuracy, and scalability.
  • Communicate insights effectively through visualizations, dashboards, and reports for technical and non-technical audiences.
  • Continuously explore new methods, tools, and algorithms in AI, ML, and predictive analytics to improve outcomes.

Required Skills & Qualifications:

  • Education: Bachelors or Masters in Statistics, Mathematics, Computer Science, Data Science, or related field.
  • Experience: 4+ years in predictive analytics, statistical modelling, or data science roles (preferably in AI or tech-driven companies).
  • Strong knowledge of statistical techniques (regression, hypothesis testing, probability, time-series, multivariate analysis).
  • Proficiency in Python / R for modelling, data manipulation, and visualization.
  • Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch) and data handling tools (SQL, Pandas, NumPy).
  • Exposure to cloud platforms (AWS, GCP, or Azure) for model deployment.
  • Strong problem-solving skills with the ability to work on structured and unstructured datasets.
  • Excellent communication skills to explain complex analytical results to business teams.

May Have

  • Experience in natural language processing (NLP), recommendation systems, or deep learning.
  • Knowledge of MLOps practices for scalable AI model deployment.
  • Familiarity with big data ecosystems (Spark, Hadoop, Databricks).
  • Publications, certifications, or contributions to AI/ML research communities

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