Decision Support

Decision Support Data Jobs

2 jobs found

Today

Senior Applied Data Scientist – Forecasting & Decision Systems

Hawaii Foodservice Alliance Honolulu, HI

Honolulu, HI

Today

$145k - $180k/yr Full time Python Senior Advanced Analytics

Apply Now

Job Description

The role centres on designing and deploying forecasting, optimization, and AI-enabled decision systems to optimize Hawaii Foodservice Alliance’s logistics operations, with a hybrid work arrangement based in Oahu.

Responsibilities

Lead the end-to-end demand forecasting capability from problem framing to production deployment, monitoring, and ongoing improvement.
Develop store-item-day forecasts that capture seasonality, promotions, intermittent demand, stockouts, product life cycles, and the asymmetric costs of over or under ordering.
Set up credible baselines, backtesting frameworks, business-weighted evaluation metrics, and controlled pilots.
Rapidly prototype analytical applications, model-review tools, and operational workflows using modern AI-assisted development platforms.
Translate model outputs into actionable recommendations for buyers, order writers, merchandisers, and operational leaders.
Build production‑level Python and SQL solutions, including batch pipelines, model services, APIs, monitoring, and decision logs.
Measure whether models produce meaningful business outcomes such as reduced distress, improved shelf availability, better ordering, and more efficient allocation of labor and resources.
Design mechanisms to capture user overrides, operational context, and actual outcomes to enable continuous system improvement.
Partner with Data Engineering and Business Intelligence to leverage and extend governed Snowflake and dbt data products.
Collaborate with Software Engineering to integrate models and decision logic into HFA’s internal applications.
Contribute to analytical datasets, KPI definitions, and dashboards that directly support the decision products you own.
Explore optimization approaches for scheduling, routing, purchasing, replenishment, and task prioritization.
Help develop AI-assisted operational monitoring that detects abnormalities, assembles supporting evidence, explains causes, and recommends next actions with human oversight.
Clearly communicate findings to both technical teams and business leaders, including when evidence does not justify deploying a model.

Requirements

At least five years of experience building applied data science, forecasting, machine learning, or decision-support systems, or an equivalent record of production ownership.
Proven ability to move models from experimentation into live business workflows.
Strong Python and SQL skills.
Practical depth in time-series forecasting with rigorous backtesting and benchmarking against simple baselines.
A scientific mindset grounded in hypothesis testing, measurement, uncertainty, and willingness to revise approaches based on evidence.
Ability to translate ambiguous business problems into measurable objectives, constraints, evaluation criteria, and an implementable product.
Experience delivering working software beyond notebooks, including applications, services, automated pipelines, or internal tools.
Experience using AI-assisted coding tools to accelerate development while maintaining tests, version control, security, and maintainable architecture.
Familiarity with production practices such as Docker, orchestration, CI/CD, model monitoring, drift detection, observability, or experiment tracking.
Ability to work directly with operational users, understand decision processes, and explain technical results in practical terms.
Strong judgment on when to apply advanced modeling versus simpler, more interpretable approaches.
Ability to operate independently while collaborating closely with data, BI, software, and business teams.

Technologies

Python, SQL, Snowflake, dbt, Snowpark, Airflow, MLflow, OR-Tools, Gurobi, CPLEX, Pyomo
React, Streamlit, Dash
Docker

Preferred Experience

Demand forecasting in grocery, retail, consumer packaged goods, food distribution, replenishment, or other inventory-intensive settings
Probabilistic or quantile forecasting, hierarchical forecasting, intermittent demand, cold-start forecasting, or demand censored by stockouts
Inventory optimization, safety stock, service-level modeling, or newsvendor-type decisions
Mathematical optimization including routing, scheduling, constraint programming, simulation, or mixed-integer programming
Experience with OR-Tools, Gurobi, CPLEX, Pyomo or similar optimization frameworks
Exposure to Snowflake, dbt, Airflow, MLflow, Snowpark or similar warehouse-centric platforms
Applied LLM or agentic-system experience with tools, structured data, business rules, and human approval workflows
Computer vision, OCR, or vision-language models
Causal inference, promotion-lift analysis, difference-in-differences, synthetic controls, or experimentation in operational settings
Experience building lightweight front ends or internal apps using React, Streamlit, or Dash
Experience with DSD, logistics, warehouse, merchandising, transportation, or multi-location field operations

What Success Looks Like

Develop a clear understanding of HFA’s ordering processes, constraints, and current forecasting methods
Establish a reproducible backtesting and evaluation framework
Replicate the incumbent baseline and identify key forecast error sources
Deliver an initial model and forecast-review prototype for a focused category or area
Show measurable improvement over the baseline on holdout data
Deploy probabilistic forecasts or order recommendations in a controlled pilot
Implement monitoring, drift detection, model versioning, and user-override logging
Set up a plan to measure distress, shelf availability, service level, and adoption
Assess operational and financial impact of the initial forecast pilot
Extend successful approaches to additional categories or locations
Establish a sustainable model development and monitoring process
Deliver or scope a second decision system such as routing, scheduling, or AI-assisted monitoring

Compensation

Salary Range: $145,000–$180,000 per year
Actual compensation determined by qualifications, production experience, technical depth, and internal equity. This range reflects the base salary for the Oahu-based role at posting time.
Candidates near the upper end typically bring production forecasting or optimization ownership, strong software development capabilities, and a track record of measurable operational impact.

Benefits & Wellness

100% employer-paid medical coverage for team members, with subsidized family coverage
Dental, vision, and preventive care benefits
401(k) retirement plan with up to 4% employer match and immediate vesting
Paid vacation, sick leave, holidays, and floating holidays
Employee Assistance Program with free, confidential counseling
Horizon Day — a paid annual day off to volunteer
Wellness programs including gym membership discounts and health initiatives
Flexible spending account
Life insurance
Paid time off

Why This Role

You will directly own a new applied-science capability and shape systems that influence real orders, inventory, routes, labor, shelves, and customer service across Hawaiʻi.
This is a hands-on role that blends scientific thinking with modern AI enabled development and strong engineering judgment to address meaningful operational problems, rather than notebook-only research or traditional reporting.

View full job page →

4d ago

Spaceflight Data Scientist

Leidos Houston, TX

Houston, TX

4d ago

$108k - $195k/yr Full time Bayesian Modeling Data Analysis Data Analytics

Apply Now

Job Description

Leidos invites applications for a Spaceflight Data Scientist for NASA JSC, onsite in Houston. This role emphasizes Bayesian decision theory and normative decision analysis to support Mars sample return and planetary protection. Travel may be required.

Benefits and culture

Competitive compensation
Health and Wellness programs
Income Protection
Paid Leave
Retirement

Location: Houston, TX (onsite). Salary: USD 107,900 - 195,050 per year.