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Data Scientist

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

Georgia (USA), North Carolina (USA), United States

Offer summary

Qualifications:

Bachelor’s degree in relevant field, 2 to 5 years data analytics experience, Experience with Python and SQL, Familiarity with Big Data frameworks, Master's or Ph.D. preferred.

Key responsabilities:

Develop machine learning models and analytics
Conduct exploratory data analysis
Report on methodology, results, insights
Interact with stakeholders for model needs
Mentor Associate Data Scientists

Cognia XLarge https://www.smarsh.com/

1001 - 5000 Employees

See more Cognia offers

Job description

As a Data Scientist at Smarsh, you will be analyzing a wide range of unstructured communications data to address problems for our customers through attentive listening, astute planning, and out of the box thinking to develop solutions and reporting results in an engaging manner.

The role will involve working with Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis.

The role offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency.

What will you do?

Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities

Data annotation and quality review

Exploratory data analysis and model fail state analysis

Methodology, results and insights reporting, including model Governance report drafting in collaboration with senior team members

Client/prospect guidance in machine learning model and analytic fine-tuning/development processes

50% exploratory data analysis and annotation

20% interaction with stakeholders to understand modeling needs

30% data science experiments and model building

What will you bring?

Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc…)

Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc…)

Understanding and Experience of NLP Techniques in traditional pipelines, metrics, process and evaluation for supervised and unsupervised learning.

Familiarity with Deep Learning techniques for NLP.

Familiarity with LLMs.

Excellent verbal and written skills

Proven collaborator, thriving on teamwork

Self-learner

Good relationship building skills

Required Education and Experience

Bachelor’s degree in Computer Science, Applied Math, Statistics, or a scientific field

Approx. 2 to 5 years experience working with data & analytics (including school)

Experience working with Python

Familiarity with SQL and noSQL databases

Knowledge of “Big Data” frameworks like Hadoop, spark and Kafka are a plus

Familiarity with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse

Experience using Git, Linux/Unix, an IDEs

Preferred Education and Experience

Master’s or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field

Have 1+ years experience working with NLP, text analytics/classification

Knowledge of NLP transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.)

Experience with natural language processing toolkits like NLTK, spaCy

Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes

Cloud computing (AWS, GCS, Azure)

About our culture

Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.