Senior Data Scientist - R01540572

Lead Data Scientist

Primary Skills

• Classification (Decision Trees, SVM), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Great Expectation, Evidently AI, Hypothesis Testing, ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Probabilistic Graph Models, Python/PySpark, R/ R Studio, Regression (Linear, Logistic), SAS/SPSS, Statistical analysis and computing, Tools(KubeFlow, BentoML), T-Test, Z-Test

Specialization

• Data Science Advanced: Data Science Lead

Job requirements

• Key Responsibilities

• Strategic Leadership: o Define the data science vision, strategy, and roadmap in alignment with business objectives. o Lead and oversee the execution of complex data science projects from inception to deployment. o Drive innovation and identify opportunities for leveraging data to achieve business goals.

• Team Management: o Manage, mentor, and develop a team of data scientists and analysts. o Foster a collaborative and inclusive team environment. o Provide technical guidance and support to team members.

• Data Collection and Processing: o Oversee the collection, cleaning, and preprocessing of large and complex datasets from various sources. o Ensure data integrity, quality, and security. o Develop and maintain scalable data pipelines and infrastructure.

• Exploratory Data Analysis (EDA): o Lead in-depth EDA to uncover insights, trends, and patterns in data. o Visualize data using advanced tools and techniques to communicate findings effectively.

• Model Development and Evaluation: o Design, develop, and implement advanced machine learning models and algorithms. o Perform rigorous model evaluation and validation using appropriate metrics and techniques. o Optimize models for performance, accuracy, and scalability.

• Model Deployment and Integration: o Oversee the deployment of machine learning models into production environments. o Ensure seamless integration with existing systems and applications. o Monitor and maintain models in production, ensuring continued performance and accuracy.

• Collaboration and Communication: o Collaborate with cross-functional teams, including product managers, engineers, and business stakeholders, to understand requirements and deliver solutions. o Communicate complex technical concepts and results to non-technical stakeholders. o Translate business needs into data science problems and solutions.

• Research and Innovation: o Stay abreast of the latest advancements in data science, machine learning, and AI. o Experiment with new tools, techniques, and methodologies to enhance existing processes and models. o Contribute to the data science community through publications, presentations, and open-source contributions. Qualifications • Education: Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field.

• Experience: o At least 7 years of experience in data science, with a proven track record of leading and delivering successful data science projects. o Experience in managing and mentoring data science teams.

• Technical Skills: o Expertise in programming languages such as Python, R, or Java. o Strong knowledge of machine learning frameworks and libraries, including TensorFlow, PyTorch, scikit-learn, and Keras. o Proficiency with data processing tools like Pandas, NumPy, and SQL. o Familiarity with big data technologies such as Hadoop, Spark, and distributed computing. o Experience with cloud platforms like AWS, Google Cloud, or Azure.

• Analytical Skills: Exceptional problem-solving skills and the ability to analyze complex datasets.

• Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders.

• Leadership Skills: Demonstrated ability to lead projects and teams, and to drive results in a collaborative environment.




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