Data Scientist

Data Scientist

6-9 years
Not Specified

Job Description

At TaskUs, we are building a world class Data Science capability to empower TaskUs Agents to to deliver improved services to its customers.In this role, with your technical experience along with mentorship and inspiring others, you will build frameworks, services, data sets, and models that drive self-service and customer loyalty up, and customer effort!
The Data Science Team helps the company make data-driven decisions towards optimizing the way work gets done for the better. We utilize large amounts of structured and unstructured data to tell its story and recommend actionable intel for the business to use. Ultimately, we empower the company toward delivering the world's best customer experience through advanced analytics.
We are in search of a data scientist that has knowledge and/or experience in the following: predictive analytics, machine learning, deep learning, optimization, and/or time series analysis. Our ideal team member is in possession of mathematical and statistical expertise but also an insatiable hunger to interpret the data, ask questions, connect the dots and figure out the story behind the data. You will join a team with similar expertise but will be given the chance to 'slice and dice' data using your preferred method with the ultimate goal of getting to the gist of data's story and eventually representing the data in a machine learning algorithm be it supervised or unsupervised learning. Typically has or is developing industry expertise alongside their core duties.Primary Responsibilities:
  • Uses machine learning & deep learning models (such as Linear Regression, Decision Trees, Random Forest, XGBOOST, ANN, CNN, LSTM etc), to drive business decisions and optimize business processes.
  • Develop and Deploy machine learning / deep learning pipelines on AWS leveraging AWS components like Sagemaker, Lambda, S3 and Redshift.
  • Develop solutions to Regression, Classification, Forecasting and NLP use cases.
  • You will be responsible for end to end machine learning lifecycle management which includes but not limited to Data Extraction, Data Wrangling, EDA, Feature Engineering, Feature Selection, Model Development, Hyperparameter Tuning, Model Evaluation and Deployment - Batch and API.
  • Should be able to leverage github to collaborate with other data scientists and use it as a source code repository to manage the work.
  • Explain the Machine Learning and Deep Learning models through frameworks like SHAP.
  • Creates visualizations that provides information on a large amount of data and educates stakeholders of the current status of their business and the reasons for their current performance
  • Puts together the data analytics and creates coherent reports/presentations for use of clients with varying degrees of technical knowledge, internally and externally
  • Manages his or her own project end to end, by creating project proposals, preparing documentation and deploying the analysis into usable form by the operations.
  • Partner and collaborate with senior stakeholders in the organization to evaluate Data Science Opportunities.
  • You will take a whole systems approach to analyze issues and implement holistic solutions by ensuring that linkages between structure, people, process and technology are made.
  • You will design and lead advancements, innovations and changes in current solution designs relating to latest advancements in machine learning, ML platforms and DS models.

Who you are:
  • At Least 6 years of experience in Data Analytics and 4+ years of experience in Data Science.
  • Formally mentored at least 3 individuals.
  • Experience in building end to end technical design of at least 5 machine learning projects.
  • Built and maintained at least 3 machine learning engineering pipeline end-to-end in production environments (includes feature engineering, model training, model scoring, model validation, model monitoring etc.)
  • Strong in evaluating multiple ML platforms and technologies as per the enterprise requirements.
  • Hands on experience in designing AWS based ML solutions and expert in leveraging AWS Sagemaker / Sagemaker studio along with feature store and model registry.
  • Familiar with the latest research and tools in machine learning, you can advise and suggest particular model types/neural network topologies for a particular domain.
  • Familiarity with tradeoffs with different model approaches, Bias vs Variance, multiple evaluation metrics etc.
  • Strong understanding of how a team's goals fit a business need.
  • Ability to identify business problems at the team level and provide solutions.

Technical Skills
  • Strong knowledge of Python, SQL.
  • Strong working experience with libraries like pandas, numpy, psycopg, nltk, spacy, scipy, boto3, scikit-learn, pyspark, tensorflow, keras etc.
  • Strong knowledge of data visualization tools such as Power BI / Tableau.
  • Experience with distributed frameworks like pySpark would be preferred.

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