Senior Data Scientist Lead

Elucidate AI

United States

Hybrid

USD 55,000 - 92,000

Full time

3 days ago
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Benefits offered by this job

Remote work options
Learning and development opportunities
Unlimited annual leave

Job summary

Elucidate AI in Johannesburg, South Africa, offers a Senior Data Scientist role with remote and hybrid options. You will lead analytical and machine learning work to translate microfinance data into actionable business recommendations and deployable solutions.

You will collaborate with data engineering and data science teams, present findings to executive stakeholders, and guide the implementation of recommendations while shaping MVP scope.

Qualifications

  • Honours-level degree in engineering, mathematics, computer science, or another STEM discipline.
  • At least three years of experience presenting analytics to business teams in a client-facing role.
  • At least three years of experience conducting analysis, generating findings, and implementing improvements.
  • Fundamental understanding of machine learning and statistics.
  • Experience manipulating data with Python; PySpark is a plus.
  • Experience with data visualization and communicating effectively with executive stakeholders.

Responsibilities

  • Lead analytical and machine learning work to convert microfinance data into business recommendations and deployable solutions.
  • Partner with data engineering and data science teams on technical and strategic priorities.
  • Analyze microfinance data and develop recommendations for business decisions.
  • Present findings and proposed actions to executive teams.
  • Guide implementation of recommendations and evaluate their results.
  • Design, build, and deploy machine learning models and statistical optimizations.
  • Investigate product feasibility, define MVP scope, and support technical development.

Skills

Python
Data visualization
Executive stakeholder communication
Client-facing analytics
ML fundamentals
Statistics fundamentals

Education

Honours-level degree in STEM (engineering, mathematics, CS, or similar)
Master's degree (advantageous)

Tools

PySpark

Job description

Data Scientist Johannesburg, South Africa; remote and hybrid options

Job details

Johannesburg, South Africa; remote and hybrid options Eligibility

Senior Experience

Not specified Employment

About this role

Role overviewLead analytical and machine learning work that converts microfinance data into business recommendations and deployable solutions. The role combines technical leadership, strategic planning, product ideation, client engagement, and communication with executive stakeholders.

Responsibilities

  • Partner with data engineering and data science teams on technical and strategic priorities.
  • Analyze microfinance data and develop recommendations for business decisions.
  • Present findings and proposed actions to executive teams.
  • Guide implementation of recommendations and evaluate their results.
  • Design, build, and deploy machine learning models and statistical optimizations.
  • Investigate product feasibility, define MVP scope, and support technical development.

Requirements

  • Honours-level degree in engineering, mathematics, computer science, or another STEM discipline.
  • At least three years of experience presenting analytics to business teams in a client-facing role.
  • At least three years of experience conducting analysis, generating findings, and implementing improvements.
  • Fundamental understanding of machine learning and statistics.
  • Experience manipulating data with Python; PySpark is a plus.
  • Experience with data visualization and communicating effectively with executive stakeholders.

Nice to haveA master’s degree and hands-on machine learning experience are advantageous. An entrepreneurial, client-focused approach and a strong interest in problem solving, product creation, and continuous learning are also valued.

Benefits and work setupRemote and hybrid work options, learning and development opportunities, and unlimited annual leave are provided.

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