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15787 Data Scientist II

Smart Data

Job Description

Job Description

 

For more than three decades, Strategic Data Systems (SDS) has been a software consultancy firm specializing in strategy, technology, and business transformation for Fortune 100 companies, mid-sized firms, and startups. At SDS, we empower our development teams to address our clients’ critical business challenges by leveraging cutting edge technologies. If you seek a workplace where your contributions are truly appreciated, then SDS is the company for you. Join us today to work alongside fellow development specialists and become a crucial part of our dynamic and cohesive community.

 

Job Title: Data Scientist

Location: Cincinnati, OH [onsite, downtown] OR Chicago, IL [Downtown, with travel to Cincinnati] HIGHLY PREFERRED: Remote EST/CST candidates will be considered

Years of Experience: 3+

CONTRACT TO HIRE - MUST BE ABLE TO CONVERT TO FTE W/O SPONSORSHIP***

TOP SKILLS:

  • Causal Inferences Experience
  • AI – Not a dealbreaker if no experience, must be willing to learn
  • Econometrics
  • Measurement processes
  • Quantify treatments back to business (How does purchasing behavior change with different treatments) 

 

What You’ll Do

  SUMMARY

We're seeking a Data Scientist to help shape the future of our AI and science capabilities. This is a senior individual contributor role for a technically strong, forward-thinking data scientist who can advance our Gen AI and causal ML capabilities, lead end-to-end development of scalable science solutions, and partner with product and cross-functional teams to drive vision and strategy in our space.

QUALIFICATIONS, SKILLS & EXPERIENCE

  • 3+ years of applied data science experience, with demonstrated progression in scope and technical complexity
  • Hands-on experience with Generative AI applications, including one or more of: LLM fine-tuning, prompt engineering, RAG pipelines, or agentic workflow development
  • Familiarity with causal ML and/or causal inference methods (e.g., CATE, heterogeneous treatment effect modeling, DiD, matching)
  • Strong proficiency in Python, SQL, and Git
  • Experience with Azure and Databricks, or comparable cloud-based data science platforms
  • Experience contributing to production-quality ML systems using software engineering best practices
  • Ability to partner with product managers and stakeholders to translate business needs into science solutions and roadmap priorities
  • Strong oral and written communication skills, with the ability to translate between technical and business audiences
  • Comfort with ambiguity—able to operate effectively in evolving problem spaces and contribute to early-stage vision and strategy
  • Bachelor's or Master's in Statistics, Data Science, Computer Science, Applied Math, Economics, or related quantitative field

 

Preferred:

  • Experience with MLOps practices including workflow orchestration, model monitoring, reproducibility, and deployment
  • Experience in retail, CPG, media, or marketplace analytics
  • Demonstrated ability to informally mentor or coach peers in technical best practices
  • Familiarity with experimentation frameworks and measurement pipelines

RESPONSIBILITIES

  • Advance our AI capabilities by designing, developing, and deploying Gen AI solutions—including LLM fine-tuning, prompt engineering, RAG pipelines, agentic workflows, and integration of Gen AI into existing measurement and science workflows.
  • Lead end-to-end development and scaling of data science solutions, from research and experimentation through productionization, ensuring solutions are robust, reproducible, and maintainable.
  • Partner with product managers and cross-functional stakeholders to shape the vision, roadmap, and prioritization of science products and capabilities in the personalization and loyalty space.
  • Contribute to the vision and early development of a holistic science layer—working to connect and consolidate scattered science capabilities into a unified, scalable framework.
  • Apply and extend causal ML and econometric methods (e.g., CATE, DiD, matching, panel methods) to support measurement, experimentation, and personalization at scale.
  • Build, maintain, and improve production ML and experimentation pipelines using sound MLOps and software engineering practices, including CI/CD, version control, testing, and documentation.
  • Research and evaluate emerging AI/ML technologies and methodologies, identifying opportunities to bring state-of-the-art approaches into production.
  • Serve as a technical leader and subject matter expert on the team, providing guidance and informal mentorship to peers and evolving into a formal mentor as junior talent joins the team.
  • Communicate complex technical findings and methodologies clearly to both technical and non-technical audiences, including leadership and product stakeholders.

 

What You’ll Get

 

SDS, Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws.

 

  • Competitive base salary
  • Medical, dental, and vision insurance coverage
  • Optional life and disability insurance provided
  • 401(k) with a company match and optional profit sharing
  • Paid vacation time
  • Paid Bench time
  • Training allowance offering
  • You’ll be eligible to earn referral bonuses!

 

 

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