Senior Data Scientist

 The Position:

The Senior Data Scientist is a multi-disciplinary specialist, working in a collaborative environment with global teams to drive client engagements. The Senior Data Scientist will work across a broad range of industries to design and build scalable Data Analytics solutions, solve business problems and create value by leveraging client data.

Responsibilities:

• Collaborate across multiple teams to provide data-driven recommendations and solutions to clients
• Work with team to quickly understand client needs, develop solutions, and collaboratively present findings to client executives
• Use industry expertise and data science experience to uncover new opportunities with clients’ data
• Analyze and model both structured and unstructured data
• Perform EDA and feature engineering to both inform the development of statistical models and generate improve model performance and flexibility
• Selecting features, building, and optimizing classifiers / regressors, etc. using machine learning & deep learning techniques.
• Design and build scalable machine learning models to meet the needs of given client engagement
• Assist in growing data science practice by meeting business goals through client prospecting, responding to proposals, identifying and closing opportunities within identified client accounts
• Work with client’s engineering teams to deploy the developed solutions

Qualifications

• 10+ years professional work experience as a data scientist or on advanced analytics/statistics projects
• Bachelors or Masters degree in Computer Science, Statistics, Economics, Mathematics, or other related field
• Excellent team-oriented and interpersonal skills, with a strong interest for consulting
• Experience in Python/R is required. Knowledge of both languages is preferred.
• Experience in working with any of the following databases – SQL server, Oracle, Teradata

Must have skills

• Outstanding communication skills with the ability to clearly articulate findings and present solutions to business partners
• Experience in Statistical modeling techniques and applied statistics
• Experience with building and deploying predictive and prescriptive analytics models
• Excellent understanding and hand-on experience of machine learning techniques and algorithms for supervised and unsupervised learning (e.g. k-NN, Regression, Naive Bayes, SVM, Decision Tree, Random Forests, k-means, PCA etc.).
• Familiarity with Cloud-based environments such as AWS (S3/EC2), Azure, Google Cloud
• Experience with data science toolkits such as NumPy, Pandas, StatModel, Scikit learn, SciPy, NLTK, Spacy, Gensim, OpenCV etc.

Optional requirements

• Experience in NLP, computer vision, sentiment analysis, topic modeling
• Good understanding of Deep-learning models for text & image analytics (such as ANNs, CNNs, LSTM, Transfer Learning, Encoder and decoder, etc).
• Experience in working with advanced machine learning libraries - Pytorch, TensorFlow, Keras and a good understanding of modelling platforms (Azure AutoML, SageMaker, DataBricks, DataRobot and H2O.ai)
• Comprehensive knowledge of AWS architecture, tools, principles and integration methods
• Knowledge and experience with designing high volume data pipelines for data lakes and data warehouses
• Experienced in defining data models
• Knowledge/ experience to execute large dataset on Hadoop, Pyspark, etc
• Some exposure to analytics/ML/AI/AIOps in support of data scientists would be a plus
• Experience as a Data Engineer on an AIOPs project would be a plus
• Experience in designing and deploying dashboards for business users
• Knowledge and experience in using BI tools like PowerBI, Tableau, Qlikview