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Principal Analyst – Data Science

Factspan Overview:
Factspan is a pure play analytics organization. We partner with fortune 500 enterprises to build an analytics center of excellence, generating insights and solutions from raw data to solve business challenges, make strategic recommendations and implement new processes that help them succeed. With offices in Seattle, Washington and Bangalore, India; we use a global delivery model to service our customers. Our customers include industry leaders from Retail, Financial Services, Hospitality, and technology sectors.
Job Responsibilities
• Selecting features, building, and optimizing classifiers/regression using machine learning and deep learning techniques
• Proficient in using data analytics tools to perform queries and analyses and for defining and correlating data, and skilled at utilizing data visualization platforms to organize and present summarizations, predictive analysis, comparative analysis, dashboards, and reporting.
• Processing, cleansing, and verifying the integrity of data used for analysis.
• Performing data mining and analytics to support ongoing continuous risk monitoring and risk assessments of operational data to recognize patterns and trends, investigate anomalies, and assess internal control environment.
• Utilize data analysis by leveraging various statistical techniques, and predictive modeling to drive and identify indicators of risk.
• Drive efficiency by automation of manual processes.
Must Have :
• Excellent understanding of machine learning algorithms, such as RandomForest, Gradient Boosting, Naive Bayes, SVM, KNN.
• Good understanding of deep learning algorithms, such as DNN, CNN, RNN, LSTM, Autoencoders.
• Deep Knowledge of ML/AI software and packages such as python: scikit-learn, Tensorflow and R: CARET, PyTorch.
• Proficiency in statistics concepts: sampling theory, descriptive statistics, probability distributions, statistical tests, dimensionality, reduction, Hypothesis testing, maximum likelihood estimators, inference, etc.
• Expertise in model validation, hyperparameter tuning, and model selection techniques such as cross validation, leave-one-out, bootstrap.
• Proficiency in using query languages such as SQL, spark.
Desire :
• Completion of an undergraduate degree in engineering and 4+ years of related experience is required.
• Services, Reporting Service, Power BI.
• Python, PySpark- Distributed Computing.
• Machine Learning, Times Series, Data Mining, Mathematical, Modeling, Probability and Stochastic Processes, Mathematical Optimization, Simulation, Algorithm Design.
• Predictive modeling experience.
• Working knowledge of the Supply chain or logistics industry and terminology.
Qualifications & Experience:
Bachelor’s/Master’s Degree in Engineering
Why Should You Apply?
• Grow with Us: Be part of a hyper- growth startup with ample number of opportunities to Learn & Innovate
• People: Join hands with the talented, warm, collaborative team and highly accomplished leadership
• Buoyant Culture: Regular activities like Fun-Fridays, Sports tournaments, Trekking and you can suggest few more after joining us

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Senior Principal Analyst (SPA) – Data Science

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Responsibilities

We are seeking a highly skilled and motivated Senior Principal Analyst to join our team. The ideal candidate will
possess a strong technical background with expertise in various programming languages and data technologies, Data
Science and Artificial Intelligence coupled with exceptional business acumen and communication skills. As a Senior
Principal Analyst, you will be responsible for leading technical initiatives, designing innovative solutions, and providing expert consultation to our clients.

Key Responsibilities:

• Develop & implement machine learning models & algorithms to extract insights from large datasets.
• Select features, build, and optimize classifiers/regressors using machine learning and deep learning techniques.
• Process, cleanse, and verify the integrity of data used for analysis.
• Perform data mining and analytics to support continuous risk monitoring and risk assessments.
• Utilize various statistical techniques and predictive modeling to drive and identify indicators of risk.
• Design & maintain effective information and data models that align with the organization’s data requirements and
objectives.
• Translate complex business problems into technical solutions and architectures.
• Develop and present Proof of Concepts (POCs) and technical client presentations.
• Mentor and provide guidance to junior data scientists and analysts.

Technical Skills:

• Advanced proficiency in Python coding for AI/ML algorithms and data analytics.
• Strong grasp of machine learning algorithms: Random Forest, Gradient Boosting, Naive Bayes, SVM, KNN.
• Deep understanding of deep learning techniques: DNN, CNN, RNN, LSTM, Autoencoders.
• Proficiency with ML/AI software and tools: scikit-learn, TensorFlow, PyTorch, CARET.
• Solid understanding of statistical concepts: Sampling Theory, Descriptive Statistics, Probability Distributions,
Statistical Tests, Dimensionality Reduction, Hypothesis Testing, Maximum Likelihood Estimators, and Inference.
• Expertise in model validation, hyperparameter tuning, and model selection techniques: Cross-validation, Bootstrap methods.
• Proficiency in data analytics tools for queries and analyses, and data visualization platforms for summaries,
predictive analyses, comparative analyses, dashboards, and reports.
• Strong command of query languages: SQL and Spark.
• Familiarity with cloud platforms such as AWS and GCP is a plus.

Qualifications:

• Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related field.
• Minimum of 10 years of experience in a similar role with recent 8 years of relevant experience.
• Relevant certifications in programming languages, data technologies, or cloud platforms would be advantageous.

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