Machine Learning / Data Science Engineer

CapTech Consulting-posted 3 months ago
$95,000 - $160,000/Yr
Full-time • Mid Level
Chicago, IL
501-1,000 employees
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CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.

  • Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  • Deconstructing client needs into data-driven processes/models and analytical measures.
  • Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  • Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  • Productionizing ML systems with a focus on optimization and scalability to satisfy clients’ requirements.
  • Growing CapTech’s Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.
  • Bachelor's degree or equivalent combination of education and experience.
  • Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  • Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  • Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  • Proficiency with containerization (e.g., Docker) and microservices.
  • Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS.
  • Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels).
  • Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  • Knowledge of DevOps and automation best practices.
  • Knowledge of statistics and statistical modeling methods.
  • Knowledge of model management and model versioning best practices.
  • Generous PTO
  • Health coverage
  • Disability insurance
  • Paid family leave
  • Learning & Development programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  • Modern Health – A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources
  • Carrot Fertility – Inclusive fertility and family-forming coverage for all paths to parenthood
  • Fringe – A company paid stipend program for personalized lifestyle benefits
  • Employee Resource Groups – Employee-led committees that embrace and incorporate diversity and inclusion
  • Philanthropic Partnerships – Opportunities to engage in partnerships and pro-bono projects
  • 401(k) Matching – Generous matching and no vesting period
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