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Mitratech

Data Scientist

Posted Yesterday
Remote
Hiring Remotely in US
3-6 Annually
Mid level
Remote
Hiring Remotely in US
3-6 Annually
Mid level
As a Data Scientist, you'll analyze data, develop models, optimize ML operations, and collaborate to integrate ML solutions, leveraging latest AI methodologies and tools.
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At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions of companies the world over.  We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun!  Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available. 

Given our continued growth, we always have room for more intellect, energy, and enthusiasm - join our global team and see why it’s so special to be a part of Mitratech! 


Job Overview: As a Data Scientist at Mitratech, you will be assisting in the development of Artificial Intelligence products. The role will involve analyzing business requirements, understanding the data available, model development, and streamlining machine learning operations.

Essential Duties & Responsibilities:
  • Data Analysis & Exploration: Collect, clean, and explore structured and unstructured datasets to uncover patterns and insights.
  • Model Development: Build, evaluate, and deploy predictive models and statistical algorithms.
  • Experimentation: Design and analyze A/B tests and controlled experiments to assess product and feature performance.
  • Business Insights: Translate analytical findings into actionable recommendations that influence business and product decisions.
  • Collaboration: Partner with data engineers, product managers, and software engineers to integrate ML models and analytical pipelines into production systems.
  • Continuous Learning: Stay up to date on new methods in machine learning, statistics, and data science tools, and apply them to improve workflows.
  • Data Quality & Governance: Establish best practices for data validation, schema management, and observability to ensure data consistency and reproducibility.
  • Performance Optimization: Profile data processes and improve throughput, latency, and scalability of ML data pipelines.
  • Collaboration: Partner with cross-functional teams to integrate ML-driven solutions into production systems.
Requirements & Skills:
  • Familiarity with vector databases, retrieval-augmented generation (RAG), or embedding pipelines.
  • Knowledgeable in privacy-preserving ML, federated learning, or reinforcement learning.
  • Experience with large-scale models (LLMs, foundation models) or multi-modal AI systems.
  • Experience with experiment design and causal inference.
  • Familiarity with big data tools (Spark, Hive, or Snowflake).
  • Background in NLP, time series forecasting, or recommender systems.
  • Proficiency in Python and Data Science libraries (pandas, NumPy, scikit-learn, statsmodels, etc.) or R.
  • Understanding of machine learning algorithms (regression, classification, clustering, etc.).
  • Experience working with cloud data environments (AWS, GCP, Azure, OCI or Databricks).
  • Excellent communication, cross-functional collaboration, and documentation skills.
  • Experience with source code management tools such as Git
Education:                   
  • Bachelor’s or Master’s in Computer Science, Machine Learning, Applied Mathematics, or related field
  • 3+  years of experience as a data scientist developing models for enterprise applications.

We are an equal opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability or veteran status.

Top Skills

AWS
Azure
Databricks
GCP
Git
Hive
Numpy
Oci
Pandas
Python
R
Scikit-Learn
Snowflake
Spark
Statsmodels

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